Optimizing Successful Outcomes for Repurposing Existing Pharmaceutical Compounds

ABSTRACT

The present invention provides a process and method for preventing and/or treating protein based diseases, including, but not limited to: Alzheimer&#39;s and other amyloid based disease groups. This method recognizes correlative similarities across genomics, phenotypic and pharmacologic analytics and data to identify a list of existing compounds as high probability targets to act as inhibitors and/or stimulants close to a disease of interest. Pertinent genetic or epigenetic variances, or protein expression anomalies, are used to assemble a list of existing compounds through the use of artificial intelligence, machine learning and algorithmic relationships. This invention applies current genomic, phenotypic and pharmacological data to leverage data previously obtained in pursuit of other disease treatments. Accordingly, the current invention collapses cycle time to discovery and dramatically reduces costs. Through this system of active compounds created from tenuous relationships exhibits an elevated probability of success. Using a selection of algorithms that coordinate relationships including, but not limited to: genomic, epigenomic, phenotypic, protein dysregulation, cultural, pharmacological, etc., data, the present invention collapses cycle time of development and dramatically reduces costs by accessing data on target rich groups of previously tested abstractly related compounds.

From prehistoric times mankind has recognized certain eating behaviorswere essential or beneficial to health. Societies began to pass alonghealthy advice to their families, clans, bands, tribes and nations toform a historical record. In the most recent millennium many writingsdescribe disease and man's responses. Modern science and publishedresearch and other reports collectively provide a vast repository ofinformation relating to the gamut of human interests, including manyplants, compounds, foods, practices and activities related to both poorand good health. The present invention recognizes this collected humantreasure and uses it as the foundational heart of a changed methodologyfor rapidly developing and identifying existing compounds to be used asnew treatments to cure diseases other than the originally intendeddisease or symptom(s).

Pharmaceutical companies have complied valuable proprietary chemicallibraries for wet-testing using high throughput screening protocols.Contract service companies also maintain their own libraries ofproprietary and well-known or off-patent compounds to provide testingfor smaller or research-downsized traditional pharmaceutical companies.Associated with each chemical in their libraries, companies have storedinformation regarding sources, synthesis, structure, spontaneousisomerization, storage conditions, purity, impurities, solubilities,stabilities, available salts, etc., including published information inpatent filings, trial data and competitive research.

Following extensive research to identify a drug target associated with atargeted disease, a wide range of organic chemicals from the librariesare tested against a target protein or modified cell usinghigh-throughput screening. Although high-throughput screeningrepresented an improvement milestone, it still has a minimal (<˜5% bymany estimates) success rate in producing a safe and effective drug.After a first high-throughput screening round, preliminary hits arerescreened to verify activity and purified to confirm the compound is asidentified. Hopefully a high-throughput screening run will producemultiple hits. These hits are analyzed for factors such as likelybio-availability, packaging stability, strength of reaction, probabilityof off-target reactions, etc. before optimization—often requiring designand synthesis of a class of higher probability compounds. Many of thescreened compounds are in reality unsuitable for successful drugdevelopment, e.g., for chemical, biological or cost reasons. Even inthose instances when one or more higher probability compounds alreadyexists in a possibly pharmaceutically acceptable format (perhaps inanother portion of the library collection), additional ramped-upsynthesis is generally required to meet needs for the subsequentextensive research.

Since the advent of computers and especially the internet new techniquesin computing and higher mathematics can now be combined to interrogateextremely large data sets in parallel. Embodiments of the presentinvention through smart application of self-referencing libraries, fuzzylogic, artificial intelligence and machine learning can be applied tocollapse typical cycle times and costs to discovery of newpharmaceuticals from decades to days and from billions of dollars tomillions. This invention teaches that use of dry research(supercomputing) as an antecedent to wet research (traditionalbiological laboratories) allows multi domains to collaborate and informone another and thereby expedite and facilitate drug discovery.

As a simplified description of this invention, a genomic abnormality,disease or symptom related to disease is recognized and selected foranalysis. In this context, the term “disease” includes any recognition,including, but not limited to: syndrome, condition, ailment sickness,disorder, etc.; the term “symptom” including, but not limited to:indication, pain, sign anomaly, phenotype, disorder, dysfunction,alternative protein splicing or mis-splicing, altered expression levelor location, etc.

A directed algorithm searches a database or group of databases to builda library of related symptoms and diseases, for example, all diseasessharing a symptom can be categorized; all symptoms, diseases, etc. thathave any correlation regardless of known or hypothetical cause. Symptomsassociated with these diseases are examined building a larger collectionof disease, symptom targets. At this stage, rather than looking at thephenotypic manifestations of disease processes, the algorithm derivesfrom the database search underlying causes of the groups of symptoms anddiseases.

Diverse records are included. For example, some records may describeproposed cures that unsuccessfully treated a symptom; some records maydescribe demographic or epidemiologic factors relating to a symptom ordisease; some records may correlate a complete genome, an expressionlibrary, mutation data or the like; some records may track changes indiet due to climate conditions; etc. Using these data, the algorithm canselect a gene or likely class or list of genes as associated with thegroup of symptoms and/or diseases. Knockout and/or transgenic mice arecreated to support a testing program using the select library of highprobability available compounds the algorithm determines from the searchof database(s) to have an observed effect on or to have an observedassociation with the gene(s)' pathway(s). The testing program jumpstartsdevelopment by identifying compounds at least tangentially or abstractlyassociated with the original disease and testing only these selectcompounds in the mouse models. Then progresses efficiently by accessingknown associations and high probability, often previously tested (inanother genre) compounds for the knock-out tests.

One outcome of this method may be that one or several compounds areidentified for the primary disease, but that as part of this process,treatments for related diseases or at least partial treatments fordiseases sharing its symptoms will be realized. Rather than starting thelaboratory discovery process at the symptom level and backtrackingthrough the relevant protein pathways and/or gene, this process aims totreat an underlying cause of disease by using compounds already shown tobe related to the symptom or disease irrespective of knowledge of themolecular interactions underlying the effect. Cloud computing andartificial intelligence applied to stored knowledge to identify highprobability targets related to the disease or diseases for repurposingusing targeted confirmation by the laboratory to compress traditionalearly stages and collapsing cycle time to discovery of efficaciousrepurposed or marginally modified, e.g., congener, drugs.

A process of identifying drugs with potential alternative uses is aknown practice and can vary in specifics and outcomes. As a firstapproximation, if two drugs are similar, they might be used to treat thesame disease. Similarly, if two diseases are similar, they might betreated with the same drug or a member of a family of drugs. But drugscan also show beneficial results across several diseases or diseasegroup exhibiting as very different conditions. E.g.: sildenafil (Viagra)was first designed for angina, and was then found to work in erectiledysfunction and pulmonary arterial hypertension; sildenafil is now beingtested in cancer. Minoxidil was developed in the 1950s as a treatmentfor ulcers but during early animal testing was nearly discarded for theside effect of vasodilation. But some trials showed it surprisinglyincreased hair growth. Minoxidil was repurposed and marketed as atreatment for baldness. Aspirin is successful as a pain reliever, but ata different dose is a prophylactic against cardiac ischemia attacks. Thefailed drug, thalidomide (for morning sickness) responsible for limbdeformities, has been repurposed as a cancer treatment.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a flow chart generally outlining one strategy forrepurposing an existing drug or optimizing a chemical/biologicalvariant.

FIG. 2 depicts a flow chart incorporating a second auxiliary compound inthe pharmaceutical composition.

Since a repurposed drug has an established trial/safety record,repurposing can be quicker and much less expensive than a new drugapproval process.

SUMMARY OF THE INVENTION

FIG. 1 uses the numeric labels as indicated below to indicate variouselements of the flow diagram.

1—SNP, repeat, deletion, etc.

1A—optional database associating genomic/genetic and disease/symptomdata

2—Disease, symptom

3—One or more medical databases

3A—Unpromising results inputted into database

3B—Promising results inputted into database

4—Outputted: associated direct, indirect, unconfirmed—genomic variances

5—Phenotypic expression database

6—Outputted: Additional associated SN Ps, deletions, repeats, etc.

7—Preparing transgenic biomodel, preferably mouse

8—Database(s) associating all available cultural remedies, formal andinformal trial results/experimentations/etc., with diseases, symptoms,genomic abnormalities, etc.

9—Outputted relevant historical treatments direct and tangential

10—Database of chemical compound recipes and proposed reactions, sourcesof raw materials and/or finished product, synthetic serviceslaboratories

11—Test compounds in identified biomodels

12—Outputted test results

13—Decision branch

14—Compounds similar to or possibly associated with (e.g., racemates,decomposition products, metabolic products, impurities, etc)

15—Developmental testing, feasibility experiments (dry or wet), etc.

16—Decision branch relevant to marketing [The decision may relate to ageneral marketing decision, decision for a particular market, decisionfor a particular disease etc. This branch may comprise multiple parallelelements.]

17—Preparing compounds, marketing materials, conducting approval trials,etc.

18—Negative result feedback

FIG. 2 uses the numeric labels as indicated below to indicate variouselements of the flow diagram.

1—SNP, repeat, deletion, etc.

1A—optional database associating genomic/genetic and disease/symptomdata

2—Disease, symptom

3—One or more medical databases

3A—Unpromising results inputted into database

3B—Promising results inputted into database

4—Outputted: associated direct, indirect, unconfirmed—genomic variances

5—Phenotypic expression database

6—Outputted: Additional associated SNPs, deletions, repeats, etc.

7—Preparing transgenic biomodel, preferably mouse

8—Database(s) associating all available cultural remedies, formal andinformal trial results/experimentations/etc., with diseases, symptoms,genomic abnormalities, etc.

8A—Database associating second or subsequent symptom, disease, variance,with the original

9—Outputted relevant historical treatments direct and tangential

10—Database of chemical compound recipes and proposed reactions, sourcesof raw materials and/or finished product, synthetic serviceslaboratories

11—Test compounds in identified biomodels

11A—Test second or supportive compound

12—Outputted test results

13—Decision branch

14—Compounds similar to or possibly associated with (e.g., racemates,decomposition products, metabolic products, impurities, etc.)

15—Developmental testing, feasibility experiments (dry or wet), etc.

16—Decision branch relevant to marketing [The decision may relate to ageneral marketing decision, decision for a particular market, decisionfor a particular disease etc. This branch may comprise multiple parallelelements.]

17—Preparing compounds, marketing materials, conducting approval trials,etc.

18—Negative result feedback

The present invention elaborates an enlightened systematic approach fordiscovering and delivering medicaments and/or therapeutic supplementformulations. Unlike the conventional approach which is founded on arecognized symptom, followed by the symptom being associated with one ormore organs or biologic systems whose component parts are assessed forlikeliness of relation to the symptom(s), this new approach makes use ofthe massive data libraries to associate related symptoms and diseasesand past chemical intervention attempts.

In accordance with convention, research projects focus narrowly on aspecific molecule, generally a protein involved in activating or turningoff a pathway. One-by-one target pathways/proteins are selected andtested in vitro, possibly crystalizing the protein molecule bound and/orunbound to a natural or potential pharmaceutical ligand. Severalgenerations of chemical library screenings may or may not be successfulin identifying an active candidate drug. Cross reactions, e.g., withhepatic enzymes or with immune cells must be screened out. When adevelopment program passes these hurdles, in vivo screens, includingcell culture and/or primary cell assays, followed by trials usingtransgenic and/or knockout animal models are designed and tested forrelation to the symptomatic disease. Eventually, therapeutic compoundsor compositions are suggested and tested for possible efficacy usuallyfirst in human cell culture and one or more relevant animal models. Oncesafety and efficacy screens are satisfactorily completed, governmentapproval is sought for larger scale human trials. Following thisstep-by-step process, phase 2 and phase 3 human trials may be initiated.This conventional approach is lengthy, costly and often unsuccessful insupplying a successful outcome.

In contrast, the present invention - though also recognizing symptoms atsome stage—applies a vastly different approach. One or more genomicvariances may be correlated with one or a plurality of symptoms.Symptom(s) associated with a particular disease is/are noted or symptomsmay be addressed in isolation. In this context the term “symptom”relates to any observable feature associated with a disease, malady,undesired health characteristic, etc. Physical, biological, chemical,behavioral traits, etc., may comprise symptoms, for example, twitch,compulsive behavior, insomnia, mRNA, nRNA, a mutation, hyperthermia,pain, growth, lesion, etc. But, instead of narrowing the focus to aspecific pathway and its dominant protein(s), tremendous power in therelation of genomic data available for the human species, but also forall life forms is used to broaden the endeavor. Nuclear genomicinformation, organelle (mitochondria/chloroplasts) genomic information,bacterial genomic information, epigenetic information, episomal genomicinformation, viral genomic information, expression profilescorresponding to the genetic information serves as one bridge tophenotypic expression manifest in the original disease of interest withnoted associations serving to widen the discovery process by introducinginto the analysis: diseases, condition, and/or symptoms sharing a traitwith the original symptom/disease of interest (SDI). Using theseassociations, existing compounds can be brought to the forefront fortesting and possible repurposing to address unmet treatment needs.

Conceptually the discovery process starts with an observable deficit ordefect. A vast collection of data loosely organized in public and/orprivate databases is examined as a system for commonplace and forabstract—unrecognized—associations between, e.g., biologic data,symptoms, related protein targets, genetic information, diseasessymptoms, families of or individual modulating compounds, pathwayrelations, splice variations, expression location and timing,cytoskeletal delivery, sequestration, secretion, etc.

A system preferred for use in the present invention comprises multiplefiles comprising data in one or several structured formats, e.g.,organized into tables, lists, labels, catalogues, spreadsheets, fieldsand the like. A single database may comprise multiple organizationalstructures which may include reference links to other databases. Thedatabase organization itself preferably should not significantlyconstrain achieving results from a data query.

Individual entries within a database may be independent or may crossreference to records within other databases comprising a system. Arecord may consist of text. However, especially when artificiallyintelligent processes are applied, records may be machine derived, forexample, a Doppler or standard ultrasonic record which may comprisedigitized expression of sound and or images with vectoring, time stampand/or other mathematic or descriptic associations. Three spatialdimensions as well as numerous non-spatial annotations may be storedwhich can be projected to form one or more discoverable patterns inrelevant dimensions to be determined in responding to the query. Datamay be formatted or reformatted into a single comprehensive record orinto multiple parallel sets for efficient query of parts or the entiretyof the database system. Resource description framework organization isoften compiled into files having the “.rdf” extension. But other formatsfor storing accessible data records or a system comprising records ofdifferent formats or even one or more record entry stored in a pluralityof formats can apply in practicing the present invention. Simple space,comma delimited, or other formats used to distinguish individual valuesin a dataset.

Format may be open or closed. Open formats are generally preferred dueto the greater number of users policing for bugs, glitches, errors, etc.A moderator will generally oversee modifications. The moderator may beor may be guided by machine learning algorithm(s). Formats may also bepartially open such as identifiable data files available to certainstakeholders as allowed or restricted by federal laws and/or otherregulations or conventions (for example: Centers for Medicare andMedicaid Service policy). All relevant policies, regulations, laws andcommon courtesies should be followed when the invention is practiced.

The National Institutes of Health and similar agencies of othergovernments (e.g., European Bioinformatics Institute US National Centerfor Biotechnology Information Swiss Institute of Bioinformatics JapaneseInstitute of Genetics Broad Institute Wellcome Trust Sanger Institutemaintain and provide access to education, community, scientific, medicalresources, etc. The US food and Drug Administration and analogousregulatory and advisory bodies collate, organize and allow public accessto health and pharmaceutical information to different degrees, withrelaxed restrictions as the data age. The present invention may use,however does not require, cutting edge or proprietary data. Theinvention makes use of relevant selections from the tremendous volume oftabulated and more abstract data to track relationships betweendiseases, symptoms treatments, etc., to progress to the next stage ofcell and/or animal testing.

Throughout the millennia, hundreds of thousands of natural compoundsbeen tested informally and more recently formally with noted results.For example, smell and taste have developed to eschew especially harmfuland/or damaging groups of compounds. Many of these groups are in ouravoidance categories simply because of their potency in modifying normalmetabolisms. However, in treating diseases, metabolic modification inper se a required result. It is almost a given that medicines taste bad.

In recent centuries “medicine” has been a valued endeavor. TheHippocratic Oath goes back two and one-half millennia! Records ofvarious forms and formats have been written and/or passed throughcultural tradition. In the most recent centuries, scientific format,controlled experimentation has produced millions of reams of data thatwhich can be incurporated into pharmaceutical development processes inaccordance with the present invention. In general, these results pertainto symptoms and improving symptomatic outcomes. Many similar symptoms,e.g., foot discomfort or pain, may be rooted under a variety of causes.Without strict regard to the most proximate cause, the present inventionin a useful embodiment applies a series of algorithmic analysesanalyzing similarities, however observed, associating various diseasetreatments and trials to shared similarity groupings, assembling a listof high probability compounds, matching these compounds with a groupingof shared similarity diseases associated with one or more variable genemarkers, generating a series of knockout/transgenic mice expressing thevariances and testing compounds from the assembled high probabilitypharmaceuticals on the mice representing the groups of varied genes.Several diseases may and preferably will be involved in the knock-outtesting. The downstream effect(s) of the gene variance (often in anon-expressed portion of the genome) and interaction with other pathwaysis not required knowledge. Avoiding the basic research involved in theexperimentation often invoked in the pharmaceutical candidate selectionprocess inherently speeds results to success and avoids costlyexperiments and expenditure of time. Efficacy thus suggested in theinexpensive knocked-out models is then tested using compounds of similarreactive groups as optimization and safety are pursued.

Popular sources throughout the world including, but not limited to:Nucleic Acid Research Molecular Biology Database Collection—over 1,500databases, World Health Organization (e.g., Traditional AboriginalMedicine Practice In The Northern Territory, The InternationalPharmacopeia), Charaka Samhita and/or Sushruta Samhita (Sushruta'sCompendium), Rerum Medicarum Novae Hispaniae Thesaurus, Ayurvedatreatises, Wikipedia, Astragalus, National Center for Complementary andIntegrative Health, Smithsonian Institution, African TraditionalMedicine Pharmacopia, Cherokee pharmacopoeia medicinal plants and herbalremedies, Nature's Pharmacopeia: A World of Medicinal Plants, Canon ofMedicine, General Medicine Vols. 1-5, The Human Genome Project, NRSP-8Bioinformatics Coordination Program, Human Genome Resources at NCBI,EMBL (European Bioinformatics Institute), The Genesis Project, NationalLibrary of Medicine, International Nucleotide Sequence Database, GenBank(National Center for Biotechnology Information), BioinformaticHarvester, Gene Disease Database, SNPedia, Ensembl (provides automaticannotation databases for human, mouse, other vertebrate and eukaryotegenomes. Ensembl Genomes provides genome-scale data for bacteria,protists, fungi, plants and invertebrate metazoa, through a unified setof interactive and programmatic interfaces (using the Ensembl softwareplatform), Flybase, Saccharomyces Genome Database, Xenbase, WormBaseParaSite, Rfam, miRBase , Protein Information Resource (GeorgetownUniversity Medical Center (GUMC)), Swiss-Prot Protein Knowledgebase(Swiss Institute of Bioinformatics), PROSITE Database of ProteinFamilies and Domains, Database of Interacting Proteins (U. ofCalifornia), Pfam Protein families database of alignments and HMMs(Sanger Institute), PRINTS (Manchester University), SUPERFAMILY Libraryof HMMs, neXtProt, InterPro, DisProt Database of experimental evidencesof disorder in proteins (Indiana University School of Medicine, TempleUniversity, University of Padua), MobiDB Database (University of Padua),Zebrafish Information Network, UCSC Malaria Genome Browser, RGD RatGenome Database, The 1000 Genomes Project, BioCyc Database Collectionincluding EcoCyc and MetaCyc, BRENDA (Comprehensive Enzyme InformationSystem, including FRENDA, AMENDA, DRENDA, and KENDA), KEGG PATHWAYDatabase (Univ. of Kyoto), MANET database (University of Illinois),PubMed, FINDbase (the Frequency of INherited Disorders database), RIKENintegrated database of mammals, Barcode of Life Data Systems,Cellosaurus, (cell lines), CTD The Comparative Toxicogenomics Database(describes chemical-gene-disease interactions), DiProDB, Dryad (arepository of data underlying scientific publications in the basic andapplied biosciences), Edinburgh Mouse Atlas, EPD Eukaryotic PromoterDatabase, MethBase Database on the UCSC Genome Browser, Minimotif Miner,Oncogenomic databases (compilation of databases that serve for cancerresearch), The Cancer Genome Atlas (TCGA), TDR Targets A, TRANSFAC,Reactome (Ontario Institute for Cancer Research, European BioinformaticsInstitute, NYU Langone Medical Center, Cold Spring Harbor Laboratory),WikiPathways, BiGG Models, Personal Genome Project: RefSeq, SNP/DiseaseDatabases, OMIM Online Mendelian Inheritance in Man, OMIM InheritedDiseases, HapMap, 23andme's database, Neuroscience Information Framework(University of California, San Diego), ConsensusPathDB, Entrez (NationalCenter for Biotechnology Information) are some examples of highlyorganized data banks that may be queried in the practice of thisinvention.

An example listing of open format sources is maintained by HUGO GeneNomenclature Committee (HGNC) which listed the following databasesJanuary 20, 2018. As of January 2018, the HGNC list is continuouslyupdated.

HUGO Gene Nomenclature Committee(https://www.genenames.org/useful/genomedatabases-and-browsers).

Human Genome Databases, Browsers and Variation Resources Database ofGenomic Variants dbVar Database of Genomic Structural Variation ENCODEProject ENCyclopedia Of DNA Elements Ensembl Human human genes generatedautomatically by the Ensembl gene builder Entrez Gene searchabledatabase of genes, defined by sequence and/or located in the NCBI MapViewer Genome Reference Consortium Putting sequences into a chromosomecontext GWAS Central centralized compilation of summary level findingsfrom genetic association studies HapMap international HapMap ProjectH-Invitational Database an integrated database of human genes andtranscripts Human Genome Segmental Duplication Database Human StructuralVariation Database 1000 Genomes A Deep Catalog of Human GeneticVariation UCSC Human Genome Browser Gateway VEGA Human manual annotationof finished genome sequence

Other Vertebrate Genome Databases and Browsers AgBase a curated,open-source resource for functional analysis of agricultural plant andanimal gene products AnolisGenome a community resource site for Anolisgenomics and genetic studies ARKdb species databases includes: Cat,Chicken, Cow, Deer, Horse, Pig, Salmon, Sheep, Tilapia, Turkey BirdBaseA Database of Avian Genes and Genomes Bovmap mapping the Bovine genomeLyons Feline & Comparative Genetics Chicken Genome Resources The DogGenome Project Ensembl genome databases for vertebrates and othereukaryotic species Entrez Gene searchable database of genes, from RefSeqgenomes, defined by sequence and/or located in the NCBI Map Viewer Fuguthe Fugu genomics project Horse Genome Project Kangaroo Genome Projectlizardbase a centralized and consolidated informatics resource forlizard research MGI Mouse Genome Informatics National Animal GenomeResearch Program Pig Genome Coordination Program Porcine GenomeSequencing Project Pig Genome Resources Rabbit Genome Resources RGD RatGenome Database Tetraodon Genome Browser UCSC Genome Bioinformatics VEGAVertebrate Genome Annotation containing manual annotation of vertebratefinished genome sequence Xenbase a Xenopus web resource ZFIN ZebrafishInformation Network

Non-Vertebrate Genome Databases and Browsers ANISEED Ascidian Networkfor InSitu Expression and Embryological Data AspGDAspergillus GenomeDatabase BeetleBase the model organism database for Tribolium castaneumCacao Genome Database Caenorhabditis Genome Sequencing Projects CandidaGenome Database ChlamydDB database for the green alga Chlamydomonasreinhardtii and related species The Cotton Genome Database DaphniaGenome Database Dendrome A Forest Tree Genome Database dictyBase centralresource for Dictyostelid genomics EcoGene the Database of Escherichiacoli Sequence and Function Ensembl Genomes FlyBase a database of theDrosophila genome GenProtEC E. Coli genome and proteome database GOBASEthe Organelle Genome Database Gramene a resource for comparative grassgenomics HGD Hymenoptera Genome Database IGGI International GlossinaGenome Initiative PomBase a scientific resource for fission yeast SGDSaccharomyces Genome Database SpBase Strongylocentrotus purpuratus SeaUrchin Genome Database StellaBase Nematostella vectensis GenomicsDatabase TAIR The Arabidopsis Information Resource VectorBaseinvertebrate vectors of human pathogen WormBase the biology and genomeof C. elegans

As a metaphorical explanation to assist in understanding the methods ofthe present invention, a first ring of information surrounding theoriginal SDI is collected. This ring comprises attributes,characteristics, hypotheses, symptoms, correlated symptoms or diseases,etc., relating directly to the SDI. Risk factors, trends in diseaseprogression, commentaries by SDI afflicted individuals and friends andfamilies may be included. A weighting system algorithm or set ofalgorithms is preferentially used to rank elements of this ring. A setcomprising each element or a set comprising predominant elements of thisfirst ring is then subjected in a second cycle of analysis therebyproducing a second ring.

This second ring will relate to the SDI through the first ring and thusshare attributes, e.g., an affected gene, a misfolded protein, anenlarged mitochondrial pool, an out of range measurement, a shift inpercentile rank, etc.—any remarkable (event deviating from normal orexpected course) characteristic becomes an element of this second ring.Analysis of this second ring can broaden out to form third, fourth,fifth rings etc. These rings need not be exclusive. E.g., an element ofsaid second ring may become an element of a third ring when indicated byone or more elements sharing the second ring. As analyses progress, amulti-dimensional picture will often result. Selective algorithms togather associations and relationship information are preferentiallyapplied at various stages in analysis to emphasize specific, highlikelihood elements to guide progress.

For example, a symptom or disease in the second, third, etc., ring mayhave been the target—intended or accidental—during a successful,partially successful and or failed clinical trial. Sub-clinicalexperiments are not ignored, but in the following example clinical trialwill be discussed to assist understanding of the process.

Data elements should not be prejudged. A failed clinical trial forexample, may have been considered a failure relating to a differentpopulation, a different symptom or disease, a different criterion forsuccess, a different standard for quality control, a loss of funding,etc., may have been a major contributing factor. Trial information mayreside as elements in, e.g., a third ring. A failed compound may berepurposed, e.g., applied to a different disease element, administeredby a different route, delivered to an identified set of patients—perhapsa subset of patients with specific criteria such as absence of aparticular mutation to avoid risks, combined with a compound to block ormitigate undesired side effects, chemically stabilized, isomericallystabilized, etc. The highlighted compounds will be those previouslyshown or expected to have a high probability to interact with one ormore of the disease symptoms. Testing may indicate one or more compoundsmay be better utilized, that is repurposed, for a disease or symptom atvariance from the initiating search.

For example, analysis may determine that a potential pharmaceutical mayhave compromised effectiveness because inflammation interferes with itsaccess to the target site. In another example, analysis may suggest areason a potential pharmaceutical was less preferred or deselected wasdue to its association with inflammation. A combination pharmaceuticalcomprising the target active compound with one or more anti-inflammatorycompounds might after expedited testing using features of the presentinvention produce a novel pharmaceutical composition with improved moreacceptable efficacy. Another example might be a compound that wasassociated in some patients with oxidative damage. One or moreantioxidants or stimulators of antioxidant activity (such as by theubiquitous GSH) might then be formulated as a novel compound toeffectively manage the targeted symptom or disease. Suchanti-inflammatory compound(s) in the pharmaceutical composition,antioxidants and/or other components may be synthetic or may be derivedfrom a natural, e.g., bacterial, fungal, plant or animal origination.Other coordinating drugs that may be useful in improving pharmaceuticalcompositions formulated in accordance with this invention include, butare not limited to: antiemetics, alpha and/or beta adrenergic activecompounds, analgesics, muscle relaxers, stimulants, caffeine, etc. Acomposition may comprise one or more compounds with multipleameliorative effects.

Repurposing may involve discarding a lead compound and elevating acandidate that in the original program was lower in the developmenthierarchy. Reasons may be varied and may have changed in the interveningtime. For example, an earlier racemate may see a single opticalenantiomer supplant it. As a historical example, modafinil is a racemicpharmaceutical with, when rapidly metabolized, potential liver toxicityrestricting its maximal concentration. The L-enantiomer is metabolizedmore rapidly a) reducing its bioavailability and because of the rapidturnover risking hepatic damage; b) the R-enantiomer is metabolized moreslowly so its biologic half-life is extended. The extended half-life isdue to a reduced affinity for and/or reduced induction of CYP3A4/5. Thisreduced rate of metabolic decomposition reduces potential and observedtoxicity. The armodafinil (R-enantiomer) thus is more effective whenadministered at the standard racemic dose due to its reduced metabolismand extended biological half-life and is less toxic for the same reason.Armodafinil is therefore prescribable at increased (and more effective)concentrations at a reduced risk to benefit ratio.

Another famous racemic distinction is that of thalidomide, where thedesired pharmaceutical effects are obtained from the S-enantiomer. It isbelieved that the R-portion of the racemate is chiefly responsible forthe drug's teratogenic effects. However, simply delivering theS-enantiomer to patients is not an option in this drug since theenantiomers autoracematize. Stabilizing the chiral center of such drugsis one repurposing example.

In similar racemic situations the present invention can provide rapidsuggestion of possible redirection of use for repurposing and maysuggest congeners with minor chemical modification, e.g., stabilizing achiral center, reducing or increasing lipid and/or aqueous solubility,etc. Additional data obtained subsequent to a failed trial (perhaps realor in silico crystallization with substrate) may suggest repurposingsuccess probability would be increased by a slight change in thepharmaceutical geometry. Although not necessary for effectiveness of theinventtion the process may be embellished by analysis of possiblecongener compounds, for example as seen with hydrocodone andhydroxycodone. Such opportunities would be discoverable in accordancewith this invention following the massive multi-dimensional processingof data. Accordingly, the present invention will not exclude opticalisomers, structural isomers, morphologic isomers, congeners or closeanalogues of the active site(s) of the candidate pharmaceutical.Morphometric analogues are also viable candidates for such analysis. Inmany cases in silico analysis for criteria including, but not limitedto: shape, solubility, active site stability, bioavailability, hepatictoxicity, thermal stability, biologic half-life, renal clearance, etc.,will operate as a first stage or screen for selecting test candidates.

Another component of the present invention may make major use of geneticinformation. Crudely, phenotypic expressions have guided past practicefor managing genetic diseases, such as sickle cell anemia, cysticfibrosis, etc. Complete or partial genomic sequence information can nowguide repurposing processes by recognizing a genetic abnormality.Frequently a phenotypic expression may not present because a parallel oralternate pathway compensates for the dysfunctional gene. Using genomicinformation in combination with other features in the database system,i.e., multiple pathway information in this example, may serve to suggestrepurposing of a failed candidate, for example, in an orphan drugenvironment, and/or may allow repurposing a generic drug to an orphandisease.

The genetic material in all its available tissue sources and formatsallows for a primary or preliminary association with a disease and oneor more of its expressed symptoms. In general human derived data will bemost relevant, but comparisons with domains found in genomes of otherorganisms may sharpen decisions relating to alternate theories. Somehuman mutations may have no discernable effect, while data analysis mayreveal unexpected correlations and possible or probable causations.

The symptoms, phenotypic expressions, resulting from different genomicfunctionalities, are considered for each disease while other occurrencesof the symptom(s) or reversal of the symptoms are analyzed in a databasestructure, the structure of which preferably permits cross-associationof a plurality of corresponding features including, but not limited to:symptom, disease, age, gender, blood type, HLA status, mass, girth,height, hair color, collection time, details of collection procedure andcomponents used, comparison to a standard, source of sample, genomicinformation, epigenomic information, cDNA, mRNA, viral component, cellhydration, individual hydration status, source of hydration, expressionprofile, stimulus prior to or coincident with producing said feature(s),bioassay information, pharmaceuticals present or halted, physiologicdata, biochemical data, nutrition status, ion balance (that may includeone or more metallic ion, pH, polyatomic ions, counterions, chargedbiomolecules, amphipathic molecules, zwitterions, etc.) imaginginformation, activity(ies) related to feature development, etc.“Corresponding features” are features attributable to a database recordwhere a plurality of features in said record are listed as beingcoincident in that record classification, for example: a person; adisease; characteristics of a symptom, disease, mutation; collectioncriteria, etc. (in essence any information associated with the source ofthe record or the record itself). Other diseases sharing one or moresymptom are noted. Biomolecules, including, but not limited to:peptides, proteins, carbohydrates, glycoproteins, lipids, phospholipids,glycolipids, nucleoproteins, nucleic acids, vitamins, alcohols,precursors, metabolites, etc., are assimilated from these data analyses.Each available level of phenotypic expression is preferably analyzed tomaximize analytical outcomes. The phenotypic expressions are mostinformative when analyzed across large populations and multiplediseases. Animal diseases, since they may derive from analogous genes ormotifs, should not be eschewed in analysis. And since animal models areoften useful and sometimes necessary for confidence in understanding ahuman disease, non-human genomic information should be consideredrelevant in many analyses.

The processes of the present invention using the “ringing” approach canbe used to recognize related diseases where multi-expression outcomesarise from a single defective gene.

For example, a variety of auto-immune diseases including, but notlimited to: diabetes, thyroid disease, multiple sclerosis, obesity,Addison's Disease, Severe Combined Immuno-deficiency, asthma, some formsof Alzheimer's Disease, Lupus, etc., have been associated with variantsof a C-type lectin domain family 16, member A (CLEC16A) gene. CLEC16Adysfunction is only a risk factor for several auto-immune diseases.Since the gene expression is one factor driving recycling of defectivemitochondria, disease might be expected to be exacerbated whenmitochondrial damage rises. Age, gender, nutrition, reactive oxygenstimulation, glutathione deficiency, etc. modulate risk. Correlationsand/or other modulating influences can be identified in silico duringpractice of the invention.

The different undesired outcomes seen with respect to, for example,CLEC16A, arise from the dynamism of the cell and organism. No chemicalreaction operates in isolation. For example, membrane potential acts asan electric field orienting charged particles such as proteins to alower energy state, i.e., tending to neutralize the electric field. Sothe simple action of alignment—no covalent bonds formed or broken willaffect alignment and position of other proteins. Alignment can be acritical feature, for example, forcing a receptor or enzyme active siteto face a particular compartment in the organism or cell of theorganism. Many different factors may influence alignment.

Another illustration is seen with chemicals that may be used indifferent reactions. First, the reaction can only occur when the tworeactants are in contact and properly aligned. For example, adenosinetriphosphate (ATP) is a high energy compound that supplies chemicalenergy to drive thousands of different biochemical reactions. By when anATP is hydrolyzed to provide energy driving another reaction, that ATPmolecule is consumed (split into phosphate and ADP) and thus everyreaction that consumes an ATP reduces the proclivity for competing ATPconsuming reactions. Similarly, cells have found many uses (differentchemical pathways and outcomes) for the antioxidant, glutathione.Reduced glutathione is a tripeptide (GSH—glutamine, cysteine andglycine) electron donor. When GSH gives up an electron and is reversiblyoxidized through formation of a disulfide bridge with another oxidizedGSH to form GSSG while reducing other possibly damaging oxidizing(including several highly damaging reactive oxygen species (ROS)),potential downstream ROS damage from that active species molecule iseliminated and total oxidative toxicity reduced. GSH is used especiallyin hepatocytes to metabolize drugs and other foreign chemicals. But,when the GSH is oxidized to break down one drug molecule, that GSHcannot process the next molecule - and must be reduced beforeparticipating in the next reaction. The enzyme involved in metabolizingthe drug molecule is while bound to the first, incapable of otherreactions. Thus, the longer the reaction takes, the greater the need forincreased supply, e.g., induction, of the metabolizing enzyme such as aCYP enzyme.

In this respect, CLEC16A has multiple effects. CLEC variants have beenassociated with disparate diseases including, but not limited to:diabetes, adrenal dysfunction, reduced bone mineral density (BMD),Parkinson's disease, multiple sclerosis, etc. Differences in diseaseoccurrences were observed to relate to gender, age, presence of variantsof other genes, previous or current use (exposure) to pharmaceuticaltreatments, etc. Several symptoms of one or more of these diseasescorrelated with one or more symptoms of other diseases. A strongautoimmune component in the reduced BMD was not obvious. But acommonality observed in these disease states is lowered O₂ consumptionand less ATP produced in affected cells. The O₂-ATP drop derives frominadequate mitochondrial metabolism.

The connection with CLEC16A was not directly apparent as pharmaceuticaltreatments for the disparate diseases were investigated. As thisfortuitous exemplary compilation of research from multiple laboratoriesgrew over decades of research, the relationships of the diseases tomitochondria and now to CLEC variants are becoming more apparent and arebeginning to govern research strategies in the family of CLEC relateddiseases. The present invention, rather than relying on time andfortuitous relationships applies a process to identify potentialrelationships.

Genomic screening and correlation analyses associated CLEC16A withmultiple and disparate autoimmune disorders leading many researchers toattempt to connect the gene, its expression patterns and products toautoimmune disease development. Review of the literature reveals thatoften only small numbers of proteins in the pathways connecting CLEC16Ato mitochondria/O₂/ATP are investigated or discussed in the majority ofpapers. Patent application WO 2004108079 A2 discusses methods fordeveloping drugs for possible use in treating Parkinson's disease as theinteraction of Neuregulin receptor degradation protein-1(Nrdp1) with theParkin protein. Overexpression of Nrdp1 significantly reduced theendogenous Parkin level in an Nrdp1 dosage-dependent andproteasome-dependent manner. More importantly, Nrdp1 ubiquitinatedParkin and catalyzed the poly-ubiquitin chains on Parkin in vitro aswell as in cells, indicating Parkin is an Nrdp1 substrate. In addition,we demonstrated that overexpression of Nrdp1 increased the production ofreactive oxygen species (ROS), which was abrogated by co-expression ofParkin. Conversely, suppression of Nrdp1 by shRNA conferred SH-SY5Ycells a lower ROS level. Together, we provided evidence thatinteractions between Nrdp1 and Parkin negatively regulated Parkin leveland affected ROS production, suggesting that Nrdp1 may play a role inParkinson's disease.

A pseudo-random snippet of various papers and findings is discussed asillustrative of the arduous processes that can be involved in relating aroot cause to a variety of downstream diseases. This brief selectionleaves out the majority of published research in the fields but providesa glimpse of the complex integrations involved in following traditionalpatterns of research for drug discovery. It is understood that mitophagyis a cellular quality control pathway essential or eliminating unhealthymitochondria. See e.g., Diabetes 2017; db170321.

Furong Yu & Jianhua Zhou (Neuroscience letters. 440. 4-8.10.1016/j.neulet.2008.) teach that Parkin is ubiquitinated by Nrdp1 andresults in abrogation of Nrdp1-induced oxidative stress. They usedinterfering RNA molecules to confirm that reduced ROS was associatedwith Nrdp1 expression and that in other cells, overexpression of Nrdp1increased ROS.

Kageyama et al (The EMBO journal, 33(23), 2798-2813) report that:Parkin-independent mitophagy requires Drp1. Mitochondria enlarge andaccumulate ubiquitinated outer membrane proteins and mitophagy adaptorprotein p62 independently of Parkin. Drp1 deficiency causesmitochondrial dysfunction. And simultaneous loss of Drp1 and Parkinworsened cardiac defects.

DECIPHER(https://decipher.sanger.ac.uk/gene/CLEC16A#overview/clinical-info)confirms the RNF41/NRDP1-PARK2 pathway regulates autophagosome-lysosomefusion during late mitophagy. [RNF41 is the gene expressing Drpt]

Durcan & Fon (Autophagy Vol. 11, Iss. 2, 2015) observe that theParkinson disease (PD)-associated E3-ubiquitin (Ub) ligase PARK2/Parkinplays a central role in many stress response pathways, and inparticular, in mitochondrial quality control. At least one form ofParkinson's disease is associated with thePARK2 gene, but otheretiologies affecting PARK2 may be involved in interrupting the mitophagypathway.

Larson-Casey et al (Immunity 44, 582-596, March 15, 2016) teach thatAkt1 induced macrophage mitochondrial reactive oxygen species (ROS) andmitophagy.

Tam et al (Exp Cell Res. 2017 Mar 15; 352(2): 304-312) describe humanCLEC16A regulation of autophagy by modulating mTOR activity.Overexpression of CLEC16A sensitizes cells towards the availability ofnutrients with a heightened mTOR activity. This diminishes LC3autophagic activity following nutrient deprivation. CLEC16A deficiency,on the other hand, delays mTOR activity in response to nutrient sensing,providing an augmented autophagic response. CLEC16A physically residesin cytosolic vesicles and the Golgi. Nutrient removal promotesclustering within the Golgi. They suggest that Golgi-associated CLEC16Anegatively regulates autophagy via modulation of mTOR activity, andthrough this route may provide support for a functional link betweenCLEC16A and autoimmunity.

Swanberg et al (PLOS ONE, 2012) report that polymorphisms in theinflammatory genes CIITA, CLEC16A and IFNG influence BMD, bone loss andfracture in elderly women.

Soleimanpour et al (Cell Volume 157, Issue 7, 19 June 2014, Pages1577-1590) teach that type 1 diabetes susceptibility gene Clec16ainteracts with E3 ubiquitin ligase Nrdp1. Clec16a via Nrdp1 regulatesautophagosomal trafficking during late mitophagy. Clec16a regulatespancreatic β cell function through control of mitophagy. Clec16acontrols β cell function and prevents diabetes by controlling mitophagy.And suggest that the CLEC16A/Nrdp1 pathway could be targeted forprevention and control of diabetes and may extend to the pathogenesis ofother Clec16a- and Parkin-associated diseases.

In a subsequent report, Soleimanpour et al (Diabetes. 2015Oct;64(10):3475-84) relate type 2 diabetes to the mix with the followingobservations: Pd×1 regulates the expression of Clec16a, a type 1diabetes gene and itself a key mediator of mitophagy through regulationof the E3 ubiquitin ligase Nrdp1. Restoration of Clec16a expressionafter Pd×1 loss of function restores mitochondrial trafficking duringmitophagy and improves mitochondrial respiration and glucose-stimulatedinsulin release. Pd×1 orchestrates nuclear control of mitochondrialfunction in part by controlling mitophagy through Clec16A.

Pearson et al (Diabetes 2017 Nov; db170321) report Clec16A, Nrdp1, andUSP8 form a Ubiquitin-Dependent tripartite complex that regulates betacell mitophagy.

CLEC is a rare available example of looking through the pathways ofseemingly unrelated diseases to begin to understand the commonalitiesand to suggest treatments closer to the root cause of the diseaseprocess. This involved decades of research in hundreds of laboratoriesand costs in the billions of dollars. The present invention still useshistorical data developed around the world at great expense but does notrequire sequential step-by-step understandings between hundreds ofdispersed researchers to assimilate seemingly unrelated or possiblyweakly related findings in a manner to more rapidly and economicallyassociate diseases with other diseases sharing a root cause or relateddysfunctional pathway.

Historical medicine including natural selection deaths, successful andfailed treatments, evidence of selective pressures, etc., constitutesanother valuable component of the optimized analytical framework.Treatments, including, but not limited to: conventional medicine,holistic, traditional, complementary, homeopathic, allopathic, etc., areassessed for relation to the original symptom(s) in question. Generally,these compounds will be known in the art and unpatentable as simplechemical material, but may be available, e.g., for repurposing in methodpatents, in combination with other compounds in compositions and/or insome cases as particular crystalline structures or at unexpectedlyefficacious concentrations. Potential compositions and/or compounds areanalyzed for their probable efficacy to the original symptom(s). Relatedsymptoms are considered, for example, those relating to oxidativedamage, ischemia, inflammation, etc., to propose optimal treatments forthe original symptomatic disease as well as other diseases with one ormore related symptom.

Previous experiences including traditional use, successful andunsuccessful medical trials, scientific literature, etc., are availablefor consideration. Many compounds will already have developed protocolsfor potential uses. Target biomolecules, cells, and then transgenic orknockout organisms can then be produced on a wide scale to assess themultiplicity of symptoms and related diseases to efficiently arrive atcompositions for live animal and then human testing and marketing.Promising compounds and/or compositions are then delivered to asymptomatic individual or to a physical, chemical and/or bio model forassessing applicability to treating relevant symptoms in an individual.Compositions may be mixtures of a plurality of chemical compoundentities in the same liquid, tablet, capsule caplet, solid matrixsubstance, etc., and may include mixtures occurring in the body andmixtures of one or more metabolites or reaction products of pluralchemical entities delivered to a recipient in a single delivery event ora timed event. The composition as defined in this application maycomprise none of the named chemical entities, instead comprising one ormore metabolic products of same.

Biotechnology has advanced greatly to allow rapid production oftransgenic and/or knockout cells and animals. Mice, being smallinexpensively reproduced mammals are often a knockout organism of choicefor screening. Mice are currently the laboratory animal species ofchoice since they are well-studied, cheap to produce the mammals mostclosely related to the humans for which the knockout technique can bepredictably applied. Knocked out animals can serve as controls foranimals whose matching gene(s) have been knocked-out and replaced by ahuman version. Genetic engineering now has the capacity to “knockout” agene or motif thereof to develop knockout cell lines or knock outanimals. Transgenes—analogous genes taken from another species (e.g., ahuman) or modified with or without a mutation of interest can beinserted rather accurately to the targeted location. Using particulartools of such technology will depend on the nature of the target.Various vectors have been used to produce knocked-out blastocysts in thepast. CRISPR/Cas9 and variations have now provided additional tools forthe skilled and possibly less skilled artisans to employ in modifyingmouse genomics.

Although perhaps 15% of knocked-out genes may be lethal, replacementwith analogous genes often overcomes this difficulty in raising theanimals to adult status.

For greatest time efficiency the transgenic and/or knockout cells ororganisms will be mass produced, i.e., in an assembly line typeatmosphere to make hundreds or more different target organisms. For mostrapid routes to the next stage in the production pipeline, the knockoutor transgenic organisms do not require painstaking and time consumingvalidation. The validation stages can be deferred until promising dataare obtained. This reduces the cost and time necessary for validatingorganisms that are not supportive of results.

While the pharmaceutical industry has successfully developed treatmentsfor a multitude of human and animal diseases, many of the treatments arenot ideal for reasons including, but not limited to: a) the treatmentscause undesired effects (side effects), b) the treatments are merelytreatments, not cures, c) the treatments have variable effectivenessacross the population, d) the treatments have a limited period ofeffectiveness, etc.

Conventional procedures for developing a new drug comprise a lengthy andcostly process. Estimates for bringing a new chemical entity (NCE) drugto market include a time frame of 10 to 15 years and a cost of $1 to $2billion. NCEs may face limitations from patent and scientific literaturedisclosure describing the chemical entity which will not be considered“novel” even though a utility may not have been envisioned.

One response from industry has been a turn to biologic molecules, forexample, antibodies as treatment compounds. The cost of developmentthrough human trials remains. But patent coverage as new compounds maybe more readily available. However, competing antibodies against thesame treatment target would also be considered novel allowingcompetitors to compete with or even replace the initial biologic.

In the absence of availability of strong patent protection, theimportance of several years “data exclusivity” (a requirement that a newcompetitor drug go through the same trial process before coming onmarket as a competitor) provides a financial support for the massivecosts for bringing new treatments to the marketplace.

An alternative approach has been a phenomenon dubbed “repurposing”.Repurposing refers to a practice of finding alternative therapeuticindications for existing chemical entities including presently marketedrugs and drugs that may have failed efficacy tests in earlier trials.Ideally, a selected drug will have already been shown to be safe. Thiscan significantly reduce the time and cost it takes to bring the drug tomarket. The earlier work regarding safety can make it more likely to getto market compared to an NCE. For a drug candidate with unsatisfactoryefficacy in one proposed use the cost savings may be less, but stillsignificant. If marketed as a supplement, the trial stage is not asrigorous, so costs are reduced. And even non-drugs, e.g., botanicals,may already be generally recognized as safe requiring no or just minimalsafety confirmation of e.g., dosage. One famous repurposed drug isViagra which failed on its testing for cardiovascular efficacy, butbecame a marketed blockbuster for its serendipitous effects on maleerections that appeared as a side effect. Rogaine had a similar failurefor its intended use, but was brought on the market to take advantage ofa side effect instigating hair growth. Other such drugs suggestingeffectiveness of repurposing include but are not limited to: Cymbalta,Gemzar, Evista, aspirin, ibuprofen, etc. Thus, this process has a provenutility and acceptability by regulators. At present in excess of 2000previously approved pharmaceutical compounds have seen their initial NCEpatent claims expire and are available for repurposing.

Despite possibly reduced costs, bring a new treatment to the publicinvolves significant expenses at the start. If competitors were free tosimply piggyback on the development and marketing of the new treatment,the absent financial incentive for improving medical treatments wouldrapidly bankrupt innovators and serve to disincentivize continuedimprovement in medicine. One incentive for repurposing can be found in“second medical use” patents that are available in many jurisdictions.In Europe two claim formats have been successful: The Swiss claim—“Useof substance X in the manufacture of a medicament for the treatment ofcondition Y” and the EPC2000 claim as a possible codified replacement oralternative—“Substance X for use in the treatment of condition Y”. Inthe US various method claims are possible as well as Jepsom “theimprovement being . . . ” claims.

Irrespective of the format of the claim, a patent for a new medical usefor a substance must be supported by evidence of efficacy. Severaljurisdictions may require safety indications as support for utility.

Another potential pitfall in the patenting is lack of novelty due toinherency, especially when the treated symptoms and/or diseases areclosely related. But attention in the description to differentiaterelated diseases and care in claim language can significantly reducerisk.

Supplements have fewer restrictions on approval and marketing in the US.But the labelling may be an issue if referring to a specific healthbenefit. Accordingly, patenting is beneficial, especially when thebeneficial outcomes are best achieved using a novel combination ofmaterials, a pro-compound that is beneficially metabolized, and/or doseranges that provide special benefit.

Another embodiment of the present invention features designing andproducing novel chemical entities for treating a disease or class orgroup of diseases. This embodiment relies on similarities in a similarfashion as other embodiments, but instead of relying just on previouslyconceived compounds, applies database assessments to compile a pluralityof compounds relating to a symptom, disease, symptoms relating to theoriginal symptom or disease and disease featuring similar symptom(s).Chemical compounds with varying degrees of success in modulating one ofmore symptoms are assessed for similarities and distinctions. Structuralfeatures of promising compounds are incorporated into a chimericcompound or library of chimeric compounds, the chimeras maintaining thepromising features while minimizing or eliminating features thataccording to database assessments were undesired for one or more reasonsas determined form database analysis.

The present invention is not restricted to these compositions withavailable market exclusivity, though in many cases these advantages willinduce producers to make and market products that increase healthyoutcomes that benefit individuals and societies.

To answer the need for developing and marketing beneficial healthsupplements and/or novel treatments, the present invention provides amulti-step approach for discovering, screening, developing, optimizingand producing new treatments for symptomatic relief and treatment ofdisease(s).

A summarized example of this aspect of the present invention starts witha sub-optimal presentation of an individual. One or more deficienciesare catalogued, e.g., a sensory, defect, a motor defect, a cognitivedefect, an adaptive defect, etc. In essence, any one or more biologicfunction(s) that is/are either hyper- or hypo- active may be addressed.Several approaches are available. For example, genomic information,including nuclear, mitochondrial, a specific tissue or organ, nucleicacid information, epigenetic information, etc., might be compared withcorresponding information of other individuals either with or withoutaspects of the suboptimal presentation. Symptoms obtained from aphysical or mental assessment may be a part of the process. Bio-assays,including, but not limited to: blood, tears, sweat, mucus, semen,saliva, skin, tissue or organ biopsy, imaging, etc., may also be used.Assessments at sequential intervals or coinciding with one or moreevents or responses may be considered. Comparisons to one or morebalancing states including, but not limited to: a “normal” or “moredesired” status of the individual(s), a related individual, anindividual presenting lesser of greater defect, a population, asub-population (e.g., by genetic background, race, location, exposure,age, gender, size, mass, activity, physical characteristic, physiologiccharacteristic, previous pharmaceutical experience, profession, paintolerance, etc.), a composite drawn from available data, etc., willoften be an advantage in optimizing therapy.

Complaints/symptoms/observations associated with a disease state arecatalogued and compared within a database collection for guidance fromprevious experiences. Specific biomolecules, often a protein, but notexclusively, may be associated with the individual's or individuals'symptom(s). One or more known chemical entity(ies) may already have ahistorical record in relation to the symptom(s) or biomolecule(s). Theanalysis need not be restricted to off-patent pharmaceuticals, withdrawnpharmaceuticals or failed pharmaceuticals, but might include anyavailable evidence including, but not limited to: conventional medicine,holistic teachings, traditional concoctions, complementary therapies,herbal medicines, homeopathic therapeutics, allopathic composites, etc.

The data may be assessed using human or machine or a combinationthereof. Artificial intelligence will become more efficacious withpractice and experiences relating to successes and degrees of successes,which may include repurposing at any stage. For chemical entities, a NCEmay be suggested by using the available data. For example, a slightchange in permeability, electron donation or withdrawal capacity,partitioning between lipid and aqueous phase, reconfiguration of abinding site to increase or decrease affinity or reversibility ofbinding, reconfiguration of a binding site to alter geometry of thetarget, may be desired outcomes which may or may not require using aNCE. In rare instances it is possible that the data will overwhelminglysuggest a single compound or combination of compounds. However, in manyinstances alternatives will present each having its own specialcharacteristics. With identified target molecules, in silico and invitro assays may eliminate or elevate alternative(s) as a screeningpass. More elegant in vitro bioassays, in vivo cellular assays, in vitrosynthetic tissue assays, ex vivo assays, in vivo cellular and/or animalassays may then be optimally applied for rapid and efficientconfirmation and/or elimination of a compound or composition fromconsideration.

The application of database analysis at the early stage will havereduced time and cost. Similar or identical treatments for otherdiseases or disease states will expectedly be suggested. Accordingly,the development assays, with enlightened funding may branch to addressother disease states. These branched programs may be accomplished by theinstigating team or subbed out with involvement of other interestedparties.

Rarely does a disease present with a single complaint or with identicalsymptoms in all affected patients. The complexity of themacro-organism's body requires multiple tissues and cell types, eachwith generally hundreds of anabolic and catabolic pathways and thousandsof distinctive reactions that must be accomplished at appropriatetiming. Accordingly, while a single protein may represent a majorelement in the disease initiation, maintenance and/or progression, othermaladies accompany the major cause or the major contributor to theapparent symptom(s).

Many bacterial diseases have been successfully cured using anti-biotics.However, bacteria constantly evolve to develop resistance(s) toanti-biotic compounds thereby forming strains requiring novel therapies.Even when a bacterial disease is eliminated, on some occasions theimmune response has produced cross-reactive antibodies that in additionto activating immune cell attacks on the bacterium also initiate immuneattacks on the macro-organism's own tissue(s). Thus an auto-immunedisease may linger following successful elimination of the pathogenicbacteria.

Viruses are micro-organisms known to cause many human diseases, such asmeasles, mumps, chicken pox, hepatitis, influenza, the common cold, etc.Viruses are considered obligate parasites because viruses require thehost cell's energy and molecular machinery to produced descendants. Toattain and maintain a cellular environment conducive for viralproliferation, the infecting viruses must strategically modulate hostcells' metabolism and physiology to favor viral production. Viralinfection thus often presents with a dramatic alteration of cellular andsub-cellular architecture and functions.

Mitochondria have become recognized as one of the key organelles in themaintenance of cellular homeostasis, metabolism, aging, innate immunity,apoptosis and other signaling pathways. At the intracellular level, thesize, shape and motility of the mitochondria being under control ofmitochondrial dynamics has become recognized as a key consideration forcontrolling many cellular processes. Mitochondria constitute apopulation of organelles that continuously fatten and/or elongate (byfusion), divide (by fission) and recycle their parts (by mitophagy). Theprocesses of fusion, fission and mitophagy set a fundamental frameworkof mitochondrial dynamics. The mitochondrial dynamics (fusion andfission) in concert with mitophagy sustains mitochondrial homeostasisand constitutes an important arm of mitochondrial control of cellhomeostasis.

The importance of mitochondria to a cell's healthy functions makesdiverting these functions an important component for efficient andeffective viral commandeering of the cell to produce new viral entities.The role of mitochondrial dynamics in viral infections is scant anddescribed only for few viruses. Mitochondria are often directly targetedby viral proteins or influenced by the physiological alterations tocellular environment during viral pathogenesis, e.g., deregulatedcalcium homeostasis, ER stress, oxidative stress and/or hypoxia.

Viruses interfere with the mitochondrial pathways and distortmitochondrial functions to facilitate viral proliferation. Viruses mayaffect mitochondrial activities including, but not limited to: fission,fusion, movement within the cell, movement between cells, Ca⁺⁺concentrations and gradients, mitophagy, cell apoptosis, production ofreactive oxygen species (ROS), control of innate immunity, etc.Mitochondria-mediated immune responses render them a target for invadingpathogens including viruses. Viruses may either induce or inhibitmitochondrial processes in a highly specific manner to optimizeproduction of viral progeny.

Ca⁺⁺ is an important factor for maintaining homeostasis and isrecognized by viruses as an important target for controlling viralproliferation. For example:

-   -   The NS5A protein of Hepatitis C Virus (HCV) causes alterations        in Ca⁺⁺ homeostasis, while the core protein of HCV targets        mitochondria and increases Ca⁺⁺.    -   Protein X of hepatitis B virus (HBV) interacts with the        mitochondrial outer membrane voltage-dependent anion channels        (VDAC) to release of Ca⁺⁺ from storage organelles mitochondria,        endoplasmic reticulum (ER), golgi into the cytoplasmic        compartment to facilitate viral replication.    -   The Nef protein of HIV interacts with IP3R to induce an increase        in cytosolic Ca⁺⁺ by promoting T cell receptor-independent        activation of the NFAT pathway relating to intracellular [Ca⁺⁺]        oscillation, that assists the viral gene transcription and        replication.    -   Ca⁺⁺ is an important factor in different stages of rotavirus        lifecycle and for stability to the virion through the NSP4        protein of rotavirus increasing cytosolic Ca⁺⁺ concentration.        The pUL37×11 protein of human cytomegalovirus (HCMV) migrates to        mitochondria to traffic of Ca⁺⁺ from the ER to mitochondria at        4-6 hrs post infection.

In addition to Ca⁺⁺ modulation, viruses control mitochondrial metabolismin other important manners:

-   -   Epstein-Barr virus (EBV) elicits increased oxidative stress in        the host cells within 48 hrs. This ROS event appears        instrumental in virus release.    -   The mitochondrial antiviral signaling protein (MAVS) is cleaved        by several viruses thereby reducing the cell's ability to        produce anti-viral interferons.    -   Polio virus viroprotein 2B controls perinuclear redistribution        of mitochondria and altered mitochondrial membrane permeability.    -   Pseudorabies virus and herpes simplex virus share an ability to        inhibit mitochondrial transport through glycoprotein B and its        effect on Miro and reduced recruiting of kinesin-1 to the        mitochondria to facilitate their movement within the cell.    -   Protein PB1-F2 of influenza A indices mitochondrially-mediated        cell-death.

Recognizing the multiple pathways involved in most diseases, includingvarious cell organelles, especially mitochondria, is an importantcomponent in optimizing disease management, treatment or cure. Thisapproach may often piggy-back on repurposing of pharmaceuticals, but, inseveral instances may merely serve to optimize existing therapy. Forexample, diseases affecting mitochondria will frequently includesymptoms relating to Ca⁺⁺ metabolism, oxidative damage and/or celldeath. Since mitochondria are primarily responsible for energetics ofthe mammalian cell, most diseases will have an overarching or underlyingmitochondrial activity.

The macro-organism comprises a multitude of cells to provide structureand function. Diseases in general affect cells, the active elements ofthe organism. The organism also is selfish in that it maintains its ownself, but is unreceptive to foreign materials, such as pathogenicorganisms that cause disease. The responsibility to eliminate theforeigner is the job of the immune system. When a cell becomes diseasedit undergoes changes that often appear as foreign to the organism. As aresult, a disease state often includes an inflammatory component.Reducing inflammation will not only reduce or eliminate one or oftenseveral disease symptoms, but will reduce swelling allowing betterblood, lymph and interstitial fluid flow. The reduced tissue volume,especially in instances where extracellular blockades, such as plaqueformations, may be present will physically disturb, i.e., serve to breakup the intermolecular bonding of the plaque, and coincidently allowimproved access of circulating fluids and cells for cleaning-upoperations.

Inflammation and other disease sequellae often affect water and saltbalance. Accordingly, optimal treatment for many diseases often willbenefit from at least a period where salt balance hormones and/or drugs,including, but not limited to: arginine vasopressin (vasotocin),angiotensin II, natriuretic peptides, vasoactive intestinal peptide,urotensin II, insulin, corticosteroids, especially aldosterone,anti-diuretic hormone, renin, diuretic and anti-diuretic drugs aredispensed, released and/or controlled.

EXAMPLES Example 1 Amyloid Deposition Diseases

Multiple individuals present with confusion. Following assessmentsymptoms correlate with those of a plaque deposition disease. A drugtargeting plaque dimerization is discovered in one of the databasedepositions. Efficacy has been proven in vitro but of little long termbenefit in vivo. Repurposing the drug compound as a compositionpharmaceutical inclusive of an anti-inflammatory which reduces swellingand allows the repurposed drug to gain better access to its target notonly slows disease progression but also shows slight regression.

Further in vitro analysis following in silico Monto Carlo likemulti-drug analysis suggests that oxidation effects contribute tooligomerization of the protein forming the plaque. Several stronganti-oxidants are tested individually and in combination in silico andthen for the most promising in silico combinations in vivo. Including anantioxidant capability in the composition shows further improvement inoutcome associated with more rapid disappearance of the plaque proteincomplexes.

However, in several instances although plaque formations regressed, thepatients show minimal improvement in mental clarity. Re-analysis usingthe database with an algorithm including an artificial intelligencecomponent suggests that the anti-oxidation effect induces expression ofanother inflammatory interleukin. It is not determinative whether thisresults from attracting a different population or different maturity ofimmune system cells. The data simply show an associative (andsuggestive) effect. The anti-oxidant in the composition is switched toan alternative that does not induce the suspect interleukin. Resultingtreatment is further optimized using the improved composition.

1A. Amyloid Deposition Structures and Interactions

Amyloid diseases belong to a class of diseases where protein is producedin excessive amounts that lead to its dimerization and furtheragglomerations thereby forming deposits that overwhelm the body's normalhousekeeping functions to eliminate the damaging deposits.

Amyloid deposits or “amyloids” are agglomerations of proteins thatintertwine after folding into 3-D configurations that allow multiplecopies of that protein and often other proteins to stick together. Inhumans, amyloids are linked to symptoms of various diseases. Suchpathogenic amyloids form when proteins lose their normal physiologicalfunctions as they precipitate to form fibrous deposits in plaques aroundcells. These deposits can disrupt the healthy function of cells,tissues, organs and organisms.

Amyloids are associated with at least 50 human diseases, including, butnot limited to: Alzheimer's disease, aortic medial amyloid,atherosclerosis, bovine spongiform encephalopathy, cardiac arrhythmias,cerebral amyloid angiopathy, diabetes mellitus type 2, dialysis relatedamyloidosis, familial amyloid polyneuropathy, fatal familial insomnia,Finnish amyloidosis, hereditary non-neuropathic systemic amyloidosis,Huntington's disease, isolated atrial amyloidosis, lattice cornealdystrophy, medullary carcinoma of the thyroid, Parkinson's disease,prolactinomas, rheumatoid arthritis, etc.

Many of these are classed as amyloidosis diseases and importantly areimplicated in some neurodegenerative disorders. Prions in which atransmissible and infectiously folded configuration becomes a templateguiding existing non-infectious protein forms to take on infectiousshape with a cascading effect.

Amyloid polypeptide chains generally form β-sheet structures that canaggregate into long fibers. They are generally polymeric as they growlarger. The floppiness of the misfoldings and absence of correctiverefoldases means that identical primary sequence polypeptides may foldinto multiple distinct amyloid conformations. The various amyloidforming proteins and protein fragments share features suggesting that atleast as a first pass through the algorithm pharmaceuticals with successin treating one be analyzed for effect on others.

Chaperonins are a class of proteins that facilitate correct folding ofproteins, thereby preventing amyloid aggregation. Chaperonins andmolecular chaperones in general may be helpful in preventing or slowingdiseases such as Mad Cow Disease. Chaperonin proteins have beenassociated with the tagging of misfolded proteins to be degraded. Sincemisfoldings are common to amyloid as well as several other diseases,chaperonins and the entire group of molecular chaperones would be ofproper interest for analysis in accordance with the present invention.

1B. Alzheimer's Disease

Alzheimer's disease (AD) is a chronic neurodegenerative diseaseaffecting >3×10⁷ persons worldwide. Early data suggested that AD wasassociated with decreased levels of acetylcholine. However,acetylcholinergic supportive medications, e.g., ACHesterase inhibitors:tacrine, rivastigmine, galantamine and donepezil, have not shown provenefficacy. Nevertheless, the historical use of such drug(s) iscontemplated as being considered during an algorithmic analysis phase ofpracticing this invention. Failed drugs may be effective with respect toother tangentially related diseases or may prove especially efficaciousor synergistic when used in a combination therapy. As an example,antibody therapies have been attempted without success, —See, e.g.,anti-Abeta42 trials reported in 2008. But a recent Biogen compound, ahumanized murine antibody, BAN2401, has had promising intermediate(18-month) Phase II results (although 12-month data failed to showenough of a change on AD assessment scores. Earlier failures have beenreported by Eli Lilly (solanzumab), Axovant (intepiridine). Aducanumab,another Biogen product is continuing development.

BACE1 inhibitors constitute another class of anti-AD drug candidates.BACE1 activity correlates strongly with amyloid deposition and appearsto belong in at least one β-amyloid synthetic pathway. Thus, BACE1effective drugs might be strong candidates for further repurposinganalysis. Moreover, BACE1 has now been implicated as a PKA inactivator.PKA is a protein whose expression increases during sleep and is invokedduring memory retention. Duplicative effects may appear during inventivetrials even when the secondary cause/pathway is not yet recognized. Suchunrecognized benefits of pharmaceutical candidates will become apparentwhen seen in metabolic pathway independent cellular/animal trials usedin late phase development in accordance with the present invention.

Fragments of Amyloid Precursor Protein (APP), a highly conserved geneexpressed in homologous forms in both vertebrates and invertebrates,constitute a primary component of β-myloid deposits (Aβ). Variousstudies have found Aβ fragments to range in size from 36-49 residues.The full-length protein depending on alternative splicings is from639-770 residues in length. In addition to alternative splicings, APP isthe target of numerous post translational modifying enzymes including,but not limited to: glycosylase, sialylase, phosphorylase,tyrosylprotein sulfotransferase, etc. Activity of these enzymes in othersymptoms/diseases is open for algorithmic consideration. Sulfation is aknown intensifier of protein-protein interactions.

APP is known to bind many proteins including, but not limited to: APBA1,APBA2, APBA3, APBB1, APPBP1, APPBP2, BCAP31, BLMH CLSTN1,] CAV1,COL25A1, FBLN1, GSN, HSD17B10, SHC1, etc. These interactive proteins arethus properly brought under consideration.

An APP fragment, Aβ42, is a zinc binding moiety, thus interactive withDNA and RNA. The coincidence that a zinc binding protease insulindegrading enzyme is related to other amyloid diseases is a feature ofproper interest. This with evidence that insulin can interruptagglomeration of Aβ in vitro strengthens the targeting relationship.

APP has a copper binding region like many peroxidases including themyeloperoxidase of granulocytes and the spleen green hemeprotein, but atpresent any activity arising from this site is not proven. But suchcharacteristic is proper to be considered in the algorithmic analysissearching for potential candidate pharmaceuticals and target conditionsor diseases. Similar conditions apply with mad cow disease, anothercopper binding protein and also a plaque forming prion. Like Aβ, aconformational change of the corresponding protein is responsible forthe class of neurodegenerative diseases known as transmissiblespongiform encephalopathies. These include but are not limited to: madcow disease in man and cow, and the human afflictions: kuru andCreutzfeldt-Jakob disease, etc. Like Aβ, the normal function of theseprion proteins in healthy tissue is unknown. However, it is known thatthe prion protein is a copper binding protein with high selectivity forCu²⁺. The link between prion protein and copper may provide insight intothe general, and recently appreciated, role of metals inneurodegenerative disease.

Tau protein when hyperphosphorylated is known to react with quiescenttau and similar binding proteins to form neurofibrillary tanglesdisrupting the cellular cytoskeleton.

A 2013 meta-analysis reported 19 genetic areas associated with AD risk.These “risk” genes (with corresponding proteins) include, but are notlimited to: CASS4, CELF1, FERMT2, HLA-DRB5, INPP5D, MEF2C, NME8, PTK2B,SORL1, ZCWPW1, SIC24A4, CLU, PICALM, CR1, BIN1, MS4A, ABCA7, EPHA1 andCD2AP.

Aβ and other misplaced/misfolded proteins are cleared by the glymphaticsystem as it removes metabolic waste from the mammalian brain,especially during sleep. The glymphatic system is analogous and parallelto the lymphatic system in clearing wastes from the central nervoussystem. Aquorins, especially aequorin 4 in the brain, are involved intransfer of water between compartments. The glymphatic system showselevated activity during sleep, especially slow wave sleep.

The relation to sleep and the ventricular involvement calls pinealfunction [a gland centrally located at the brain base by the third andfourth ventricles] into consideration. The pineal is an important factorin circadian rhythm and controls many cyclic activities relating to thediurnal cycles and sleep phasing. This relationship through the pinealto optic receptor pathways brings up another relevant branch to followin relating drugs and symptoms.

Expression and secretion of cystatin C, a major cysteine protease,correlates with neurodegeneration in animal models. In humans, cystatinc has been linked to neuro-degeneration in the presence of tangles withtau. However, some studies in are supportive that at least at somelevels of cystatin c involvement it may slow agglomeration and has beenobserved complexed with soluble—non-pathogenic Aβ. The cysteine proteaseactivity of intact cystatin c may be protective, but at higherconcentrations or in cystatin c variants more prone to dimerization andagglomeration the contribution to Aβ deposits and Alzheimer's typedementias may outweigh the benefits.

These examples above are merely illustrative, a product of a singlehuman making connections in a short time period. Many unmentionedrelationships may be obvious to one or several readers of thisdiscussion. However, the invention is designed to improve over theabilities of a single person or group of persons in recognizingconnections. A starting algorithm and continuing artificial intelligence(AI) involvement will improve pattern recognition acrosspharmaceuticals, diseases, symptoms, tolerances, etc. Current basic AIrelying simply on pattern recognition will immensely improve therepurposing processes outlined in this specification. AS AI furtherimproves, the process will further improve, saving time, costs andlivelihoods.

Example 2

An individual presents with a sleep disorder including a form of apnea.Treating the sleep disorder using a generic drug is partially effective.However, apnea persists. Database analysis suggests using an alternativepharmaceutical that has been tested for hypertension due to its effecton water and salt balance. Anorexic insomnia was one of the side effectsleading to its dismissal as a viable drug candidate for hypertension.This drug however is successfully repurposed for controlled andpredictable sleep pattern with the added advantage of reducingobstructive apnea through improved water retention balance.

Although the individual demonstrates improved sleep habits, her energylevels are sub-normal. Oxygen metabolism is also-subnormal. Acomposition combining the wakefulness balancing drug with amitochondrial supporting cocktail restores activities to within thoseconsidered within a normal range.

Example 3

An individual presents with a cutaneous rash. Blood and skin bioassayssuggest an autoimmune condition. Immune suppression involvingprednisolone commences. Dosing is adjusted as the conditions showsimprovement. But complete weaning is not successful. Further testing andalgorithmic analysis using the database system shows an association witha mitochondrially induced hyper-oxidative state wherein oxidized proteincomponents continue to stimulate the immune system rendering ithypersensitive to harmless metabolite components the body is in theprocess of eliminating. The algorithm followed by in silico testingsuggests balancing glucose oxidation in mitochondria should reducesuperoxide production which analysis suggests is the free-radicaloxidative donor at the root of the problem. A composition pharmaceuticalinitially inclusive of the steroid anti-immune hormone is delivered tothe individual. As successful treatment progresses a modifiedcomposition improved by reference to the database system using serialbioassays from the individual eliminates the steroid hormone but retainsa combination of mitochondrial support drugs and supplements.

Example 4

The numerals in this example correspond to those appearing in FIG. 1. Afirst skilled artisan becomes interested in a genetic variant 1 andobserves that the variant correlates with disease “a”. A second skilledartisan becomes interested in disease “b”. 2 The first may optionallyaccess database 1A to associate said variant with a disease “c”, toconfirm correlation with “a” or to confirm correlation with a pluralityof diseases “a”, “c”, “d”, etc. Similarly, the second may access 1A insearch of one or more genetic, epigenetic and/or genomic variant(s).However, either may without association of said variant to a symptom ordisease, or without an association with a variant, may access one or aplurality of medical information containing databases 3 to output abroad assessment of directly related, indirectly related, merelycorrelated (positively or negatively), anecdotal, and/or unconfirmedgenomic variances 4. The inputs into 3 and/or its outputs are thenqueried into a phenotypic expression database 5 which outputs additionalassociated variance 6. The variances from 1 or 6 are then formed into astable vector for production of at least one biomodel for each 7.Controls may be broadly applied or may be designed for an individualbiomodel or group of biomodels. In parallel a remedies database 8 isaccessed to output a listing of behavioral, chemical, and dietary datarelevant to the disease(s), symptom(s), variance(s), etc. 9 that may beassessed in an instructional database 10 or delivered to the testingelement 11. The testing element 11 may receive inputs as a pass throughfrom 9, e.g., seasonal or time or date, after meal, before bedtime,etc., may receive directions or suggestions on how to obtain compounds10 and/or suggestions of similar or related compounds 10 or 14, to becombined with the biomodels produced 7. The outputted test results 12are acted upon in accordance with decision element 13. Resultsconsidered to lack promise follow path 3A to further augment thecollected medical information, while results considered promising followa branched path 3B with one branch augmenting database 3 and a secondbranch possibly i) feeding into a compound database or algorithmicallycreated database to feed additional testing components into 11 and ii)feeding into a testing element 15 whose results guide the decision ofelement 16 to either forward a product towards marketing 17 or not 18.In either instance Database(s) 3 are further augmented. Depending on theproduct undergoing process 17, additional regulatory processes may berequired or desired but are not separately featured in this FIG. 1depiction.

Example 5

FIG. 2 shows a variant of example 4 wherein a multi-componentcomposition is carried through the development process. The numerals inthis example correspond to those appearing in FIG. 2.

Since at its outset a disease may provoke a metabolic imbalance that isusually managed by the organism's self-curative rebalancing capacities,a variance may not be obvious in a fraction of or in even a majority ofinstances of occurrence, a treatment may not always be advised;Hippocrates apparently acknowledged this with his oath. But thesecorrective metabolic pathways may be interactive with a second varianceor be ineffective in some environments. A remedy not directly connectedto the first noted variance may therefore be found ameliorative. Thepresent invention does not require determination of direct and/orindirect relationships of the first noted variance to symptoms, ratherthe present invention simply requires evidence of beneficial effect.

This example addresses this tenuous relationship but also acknowledgesthat downstream corrections, while possibly preserving life, may notdeliver optimal outcomes. Fig.2 incorporates two additional elements toillustrate one facet of this philosophy.

In addition to symptom “b₁” of disease “b”, a symptom “b₂” may also berelevant. Often a pharmacologic strategy will attempt to decipher theunderlying deficiency and follow its repercussions in pursuit of aproduct that solves the disease at its source. This involves multipledisciplines and many layers of testing. This conventional approach is adriver of high development costs and commitment of large sums of moneylengthy time to get a product to the patient and the pharmaceuticalmarket. In Example 5 a first symptom is assessed through introductioninto database 3. A second symptom follows a second path depicted asincluding database 8A. The 8A path may essentially parallel the pathfollowed using 3 but may have other inputs. When paralleling 3 theoutput might be considered as an almost independent path for treatingtwo symptoms or diseases. As an analogy, a person in a car accident mayhave a broken bone reset and a laceration closed perhaps on differentlimbs.

But example 5 also includes other considerations. For example, whenmultiple pathways are perturbed, “b₁” for example may be synergisticallyimproved through a combination therapy. One proposed specific exampleinvolves the blockade of further amyloidosis as treatment for “b₁” andan anti-inflammatory treatment to ameliorate “b₂”. In FIG. 2 this isexemplified by the database 14 feeding a related compound into thedatabase 8A. In some embodiments 8A output is further analyzed throughthe pathway following 5. 8A may also feed through directly into 10. Thecompounds of 8A are subjected to testing as depicted by 11A and thenincorporated as a composition comprising a plurality of therapeuticcompounds through the test element 11 and beyond.

Example 5 is merely an example of the reiterative serial and parallelpaths that depending on the complexity of the biology might be desiredduring an optimization process. A portion of the optimization may beapplied to existing pharmaceutical treatments, including a firstpharmaceutical treatment that may have been arrived at using fewerbranches in the beneficial, but improvable, flow process.

Component Examples

The following lists of compounds are provided as suggestive examples ofthe types of pharmaceutical and supporting compounds that might berevitalized in some instances and incorporated as especially beneficialsupporting components in therapeutic compositions.

Anti-oxidant and/or compounds that help maintain native protein foldingconformation and protein-protein interactions include but are notlimited to: thiol donors including, but not limited to: L-cysteine andN-acetylcysteine and analogues and metabolic precursors thereof,glutathione (GSH), coenzyme Q10 (CoQ10), α-lipoic acid, generally weakerbut effective antioxidants including, but not limited to: THC,phytochemicals such as resveratrol and flavonoids, milk thistle, gingko,biloba, gotu-kola, different forms of bioflavonoids, 1,2dithiolane-3-pentanoic acid, lipoate (α-LA⁻), dihydrolipoate (DLA⁻),vitamin E, vitamin C, riboflavin (B₂), L-creatine, L-arginine,L-carnitine, cyclosporin A, manganese, magnesium, zinc, carnosine,folinic acid, dichloroacetate, succinate, etc.

Prostaglandins (PG) e.g., PGA, PGA₂, PGB, PGB₂, PGC, PGD, PGD₂, PGE,PGE₁, PGE₂, PGE₃, PGF_(α), PGF₁α, PGF₂α, PGF₃α, PGG, PGH, PGH₂, PGI,PGJ, PGK, and related biomolecules, including, but not limited to:prostacyclins, thromboxanes, prostanoic acid, 2-arachidonoyl-glycerol(an endocannabinoid), etc., and their inhibitors may be especiallyuseful in specific targeting of diseases, symptoms and/or co-existingdisease states, especially when in conjunction with several specificinhibitors relating to PG synthesis or blocking in general or only inselectively specific tissues wherein a therapeutic compound maypreferentially be effective in tissues to which it can gain access or intissues which express the isoform of the enzyme that the COX or similarinhibitor targets.

Resveratrol is a potent antioxidant with apparent involvement inmitochondrial biogenesis. Resveratrol acts through AMPK and SIRT1 and isinvolved in PGC-1α. α-lipoic acid is associated with rejuvenation andreplacement of damaged mitochondria. This renewal becomes more prevalentas mitochondria age. DCA stimulates oxidative phosphorylation byinhibiting pyruvate dehydrogenase kinase. Succinate is an intermediatein the tricarboxylic acid cycle (making ATP), and participates ininflammatory signaling. Succinate dehydrogenase participates in electrontransport as part of mitochondrial “Complex II”. Melatonin demonstratescell protectant activity though slowing apoptosis as it controlsactivity of aged or oxidatively stressed mitochondria involvement inleading the cell down the apoptotic pathway. The anesthetic, cocaine,has been observed as modifying Complex I activity in mitochondria.

Increased glutathione is known to protect mitochondria and the cellagainst damaging effects of the oxidative moieties produced inmitochondria such as: superoxide anion radical O₂ ⁻, hydrogen peroxide,H₂O₂, and the extremely reactive hydroxyl radical .HO. Increasingintracellular glutathione content is possible by several methodsincluding, but not limited to: supplying precursors for glutathionesynthesis, e.g., N-acetylcysteine; increasing CoA, for example, bysupplying its precursor pantothenic acid; making curcumin (a spice)available to the cell; and the analgesic drug flupirtine. Sinceglutathione is seen to increase throughout the cell, the antioxidantprotection is not limited to the mitochondria.

β-carotene, lycopene, lutein, astaxanthin and zeaxanthin are popularcarotenoids. These biochemicals demonstrate antioxidation properties.These tend to be lipophilic and thus often are found partitioned inmembranes.

Phytoantioxidants, especially cannabinoids which may demonstratemultiple effects, including, but not limited to: cannabigerolic acid(CBGA) (antibiotic); cannabigerolic acid monomethylether (CBGAM);cannabigerol (CBG) (antibiotic, antifungal, anti-inflammatory,analgesic); cannabigerol monomethylether (CBGM); cannabigerovarinic acid(CBGVA); cannabigerovarin (CBGV), cannabichromenic acid (CBCA);cannabichromene (CBC) (antibiotic, antifungal, anti-inflammatory,analgesic); cannabichromevarinic acid (CBCVA); cannabichromevarin(CBCV); cannabidiolic acid (CBDA) (antibiotic); cannabidiol (CBD)((antioxidant, anxiolytic, antispasmodic, anti-inflammatory, analgesic);cannabidiol monomethylether (CBDM); cannabidiol C₄ (CBD-C4);cannabidivarinic acid (CBDVA); cannabidivarin (CBDV); cannabidiorcol(CBD-C1); Δ⁹-tetrahydrocannabinolic acid A (THCA-A);Δ⁹-tetrahydrocannabinolic acid B (THCA-B);6a,10a-trans-6a,7,8,10a-tetrahydro-6,6,9-trimethyl-3-pentyl-6H-dibenzo[b,d]pyran-1-ol, (Δ⁹-tetrahydrocannabinol,THC) (analgesic, antioxidant, antiemetic, anti-inflammation);Δ⁹-tetrahydrocannabinolic acid-C4 (THCA-C4); Δ⁹-tetrahydrocannabinol-C4(THC-C4); Δ⁹-tetra-hydrocannabivarinic acid (THCVA);Δ⁹-tetrahydrocannabivarinic (THCV); Δ⁷-cis-isotetrahydr-ocannabivarin;Δ⁹-tetrahydrocannabiorcolic acid (THCA-C1); tetrahydrocannabiorcol(THC-C1), Δ⁸-tetrahydrocannabinolic acid (Δ⁸-TCA);Δ⁸-tetrahydrocannabinol (Δ⁸-THC), cannabicyclol (CBL);cannabicyclolicacid (CBLA); cannabicyclovarin (CBLV), cannabiesoic acidA (CBEA-A); cannabiesoic acid B (CBEA-B); cannabieson (CBE),cannabinolic acid (CBNA); cannabinol (CBN); cannabinol methylether(CBNM); cannabinol-C4 (CBN-C4); cannabivarin (CBV); cannabinol-C2(CBN-C2); cannabiorcol (CBN-C1); cannabinodiol (CBND); cannabinidivarin(CBDV), cannabitriol (CBT);10-ethoxy-9-hydroxy-Δ-6a-tetrahydrocannabinol (10-EHDT);8,9-dihydroxy-Δ-6a-tetra-hydrocannabinol (8,9-DHDT); cannabitriolvarin(CBTV); ethoxy-cannabitriolvarin (CBTVE), dehydrocannabifuran (DCBF);cannabifuran (CBF); cannabichromanon (CBCN); cannabicitran (CBT);10-oxo-Δ-6a-tetrahydrocannabinol (OTHC); Δ⁹-cis-tetrahydrocannabinol(cis-THC);3,4,5,6-tetrahydro-7-hydroxy-α-α-2-trimethyl-9-n-propyl-2,6-methano-2H-1-benzoxocin-5-methanol(2H-iso-HHCV); cannabiripsol (CBR); trihydroxy-Δ⁹-tetrahydrocannabinol(triOH-THC) may be especially efficacious in compositions that benefitfrom anti-oxidative support.

Phytoantiinflammatory compounds are numerous and include but are notlimited to: curcumin, colchicine, resveratrol, capsaicin,epigallocatechin-3-gallate, quercetin. Numerous small molecule andbiomolecule anti-inflammatory compounds have been proposed for clinicwith varying successes. See, e.g., An update on Anti-inflammatoryCompounds: A Review. The contents of which are hereby incorporated byreference.

1. An improved method for repurposing a known compound for use intreating a disease for which said compound was not clinically prescribedcomprising: a. Initiating process by identifying a genomic variance; b.Inputting said variance into a database system; c. Outputting a list ofmedical correlates, showing a relation to said variance; d. Inputtingsaid list into a database system; e. Applying an artificiallyintelligent algorithm in outputting a second list of correlatescomprising at least one feature selected from the group consisting of:genomic variances, cultural associations, location of medical events,chemical modulations, homeopathic modulations, cultural knowledge,timing of correlation event and treatment outcome; f. Optionallyreapplying said artificially intelligent algorithm to expand or focussaid second list; g. Optionally applying a second artificially algorithmto said output product of e to expand or focus said second list; h.Repeating f and/or g as desired—including 0 times, if desired, andoutputting said result(s); i. Obtaining one or more biomodels comprisinga genomic variance or product of a genomic variance identified in aand/or h; j. Applying a compound or composition identified in h to atleast one said biomodel; k. Associating said genomic variance of saidbiomodel of j with a disease or symptom and scheduling further testingof said compound or composition with said disease or symptom; and l.Supporting marketing for pharmaceutical or supplemental use of at leastone said compound or composition whose testing exhibited positiveresult.
 2. The improved method of claim 1 wherein said location isselected from the group consisting of: a geographic location, analtitude a vehicle, an organ, a tissue, a part of the anatomy and abiopsied sample.
 3. The improved method of claim 1 wherein said one ormore biomodels comprises at least one transgenic mouse.
 4. The improvedmethod of claim 1 wherein said supporting comprises filing a patentapplication.
 5. A method of identifying a compound that modulates atleast one of a group of diseases, said method comprising: a. selectingi) a symptom or disease or ii) genomic variance; b. feeding i) or ii)into a search field of a structured database; c. querying said at leastone structured database for content of one or a plurality of recordsreferencing i) or ii); d₁. for i) selecting at least one recordreferencing a first genomic variance: d2. for ii) selecting at least onerecord referencing a first symptom or disease; e. correlating results ofd_(x) (where x=1 or 2) with at least one recorded feature of said atleast one record; f. querying at least one structured database forcontent of one or a plurality of records referencing said at least onerecorded feature; g. listing one or more compounds and/or compositionsrelated to controlling or attempting to control at least one symptomnoted as a recorded feature in said one or a plurality of recordsreferencing said at least one recorded feature; h. identifying in saidlisting, and delisting compounds and/or compositions, if any, known tohave been applied to controlling said at least one symptom; and: i.delivering to a physical, chemical and/or biomodel at least one said oneor more compounds and/or compositions, said at least one said one ormore compounds and/or compositions listed in g and remaining after h; j.determining effect of said one or more compounds and/or compositions; k.selecting one or more compounds and/or compositions determined to havedesired effect; and l. identifying at least one of one or more compoundsand/or compositions selected in k as said new pharmaceuticalcomposition; or: j. selecting at least one alternate compound orcomposition, at least one of said compounds and/or compositions delistedin h; k. optionally: noting one or more undesired outcome(s), if any,resulting from said at least one alternate compound or composition beingapplied to controlling said at least one symptom; l. selecting at leasta second compound or composition to counteract at least one of said oneor more undesired outcome(s); m. confirming desired activity of said atleast one second compound or composition; and n. identifying as said newpharmaceutical composition, a composition comprising at least one saidalternate compound to be used in conjunction with at least one saidsecond compound said one or more compounds and/or compositions.
 6. Amethod of identifying a compound that modulates at least one of a groupof diseases, said method comprising: d. selecting i) a symptom ordisease or ii) genomic variance; e. feeding i) or ii) into a searchfield of a structured database; f. querying said at least one structureddatabase for content of one or a plurality of records referencing i) orii); d₁. for i) selecting at least one record referencing a genomicvariance: d₂. for ii) selecting at least one record referencing asymptom or disease; m. correlating results of d_(x) (where x=1 or 2)with at least one recorded feature of said at least one record; n.querying at least one structured database for content of one or aplurality of records referencing said at least one recorded feature; o.listing one or more compounds and/or compositions related to controllingor attempting to control at least one symptom noted as a recordedfeature in said one or a plurality of records referencing said at leastone recorded feature; p. identifying in said listing, and delistingcompounds and/or compositions, if any, known to have been applied tocontrolling said at least one symptom; and: q. delivering to a physical,chemical and/or biomodel at least one said one or more compounds and/orcompositions, said at least one said one or more compounds and/orcompositions listed in g and remaining after h; r. determining effect ofsaid one or more compounds and/or compositions; s. selecting one or morecompounds and/or compositions determined to have desired effect; and t.identifying at least one of one or more compounds and/or compositionsselected in k as said new pharmaceutical composition; or: o. selectingat least one alternate compound or composition, at least one of saidcompounds and/or compositions delisted in h; p. optionally: noting oneor more undesired outcome(s), if any, resulting from said at least onealternate compound or composition being applied to controlling said atleast one symptom; q. selecting at least a second compound orcomposition to counteract at least one of said one or more undesiredoutcome(s); r. confirming desired activity of said at least one secondcompound or composition; and s. identifying as said new pharmaceuticalcomposition, a composition comprising at least one said alternatecompound to be used in conjunction with at least one said secondcompound said one or more compounds and/or compositions.
 7. A method foridentifying a new pharmaceutical composition for treating a disease,said method comprising: a. selecting a first symptom or a first genomicvariance; b. optionally: querying a database for a correlativerelationship between said first symptom and a correlate genomic varianceor between said first genomic variance and a correlate symptom; c.querying at least one database with at least one selection of a and/orat least one correlate of b to provide an identification of a firstdisease; d. accessing at least one structured database; e. querying saidat least one structured database for content of one or a plurality ofrecords referencing said first disease; f. selecting at least one recordreferencing said first disease; g. correlating said first disease withat least one recorded feature of said at least one record; h. queryingat least one structured database for content of one or a plurality ofrecords referencing said at least one recorded feature; i. listing oneor more compounds and/or compositions related to controlling orattempting to control at least one symptom noted as a recorded featurein said one or a plurality of records referencing said at least onerecorded feature; j. identifying in said listing, and delistingcompounds and/or compositions, if any, known to have been applied tocontrolling said at least one disease; and: k. delivering to a physical,chemical and/or biomodel at least one said one or more compounds and/orcompositions, said at least one said one or more compounds and/orcompositions listed in i and remaining after j; l. determining effect ofsaid one or more compounds and/or compositions; m. selecting one or morecompounds and/or compositions determined to have desired effect; and n.identifying at least one of one or more compounds and/or compositionsselected in I as said new pharmaceutical composition; or: k. selectingat least one alternate compound or composition, at least one of saidcompounds and/or compositions delisted in j; l. optionally: noting oneor more undesired outcome(s), if any, resulting from said at least onealternate compound or composition being applied to controlling said atleast one symptom; m. selecting at least a second compound orcomposition, said at least one second compound or composition selectedto contribute modulation of said one or more undesired outcome(s); n.confirming desired activity of said at least one second compound orcomposition; and o. identifying as said new pharmaceutical composition,a composition comprising at least one said alternate compound to be usedin conjunction with at least one said second compound said one or morecompounds and/or compositions.
 8. The method of claim 5 furthercomprising: m. or o. delivering said new pharmaceutical composition toat least one individual.
 9. The method of claim 6 further comprising: o.or p. delivering said new pharmaceutical composition to at least oneindividual.
 10. The method of claim 8 wherein said delivering comprisesproviding an individual with a substance selected from the groupconsisting of: pill, tablet, osmotic pump, ointment, inhalant, eye drop,sublingual substance, mouthwash, pastille, gel, hydrogel, injection,subdermal implant, powder, emulsion, elixir, gum, cream, paste,liniment, liposome, skin patch, suppository, IUD, microsphere,nanosphere and nasal spray.
 11. The method of claim 9 wherein saiddelivering comprises providing an individual with a substance selectedfrom the group consisting of: pill, tablet, osmotic pump, ointment,inhalant, eye drop, sublingual substance, mouthwash, pastille, gel,hydrogel, injection, subdermal implant, powder, emulsion, elixir, gum,cream, paste, liniment, liposome, skin patch, suppository, IUD,microsphere, nanosphere and nasal spray.
 12. The method of claim 5wherein at least one of said at least one undesired outcome(s) isselected from the group consisting of: countering said one or moreundesired outcome(s) (optionally, if any), anti-oxidation,anti-inflammation, diuresis, anti-diureses, anti-depression,hypertension, hypotension, naturesis, anti-naturesis, kalesis,anti-kalesis, mitochondrial fission, mitochondrial fusion, mitochondrialmotility, ROS damage, 0₂ consumption and interferon production
 13. Themethod of claim 6 wherein at least one of said at least one undesiredoutcome(s) is selected from the group consisting of: countering said oneor more undesired outcome(s) (optionally, if any), anti-oxidation,anti-inflammation, diuresis, anti-diureses, anti-depression,hypertension, hypotension, naturesis, anti-naturesis, kalesis,anti-kalesis, mitochondrial fission, mitochondrial fusion, mitochondrialmotility, ROS damage, 0₂ consumption and interferon production
 14. Amethod for producing a new pharmaceutical composition, said methodcomprising: a. selecting a first symptom of a first disease; b.providing an identification of said first disease; c. accessing at leastone structured database; d. querying said at least one structureddatabase for content of one or a plurality of records selected from thegroup consisting of: record(s) referencing said first symptom andrecord(s) referencing said first disease; e. selecting at least onefirst record obtained from d; f. selecting at least one chemicalcompound relating to said at least one first record; g. querying atleast one structured database for content of one or a plurality ofrecords referencing said at least one chemical compound to obtain alisting comprising diseases and symptoms relating to said compound; h.querying at least one structured database with results of said listingobtained from the query in g to obtain a compilation of compoundsassociated with symptoms or diseases of said listing; i. analyzingcompounds related in f. and h. for similarities and distinctions; j.querying at least one structured database for negative assessments ofcompounds related in f. and h.; k. correlating negative assessments withsimilarities and distinctions of i.; l. associating chemical structurewith said similarities and distinctions; m. selecting chemicalstructural features minimizing said negative assessments; n. designing achimeric compound or a library of chimeric compounds maintaining atleast one feature of at least one compound related in f. and h. whilediscarding one or more chemical feature selected in m.; and o. producingat least one compound designed in n.
 15. The method of claim 14 furthercomprising: e1. querying at least one structured database for a compoundpreviously applied to modulate at least one characteristic associatedwith said first symptom or said first disease to obtain a compoundidentifying record; and in f. selecting a chemical compound relating tosaid compound identifying record.
 16. The method of claim 5 furthercomprising correlating said symptom or disease with at least one genomicvariant, constructing a knock-out biomodel of said genomic variant fortesting said new pharmaceutical composition.
 17. The method of claim 6further comprising correlating said symptom or disease with at least onegenomic variant, constructing a knock-out biomodel of said genomicvariant for testing said compound designed in n.
 18. The method of claim5 further comprising correlating said symptom or disease with at leastone genomic variant, constructing a knock-out biomodel of said genomicvariant for testing said new pharmaceutical compound or composition. 19.A pharmaceutical composition identified in accordance with claim
 5. 20.The composition of claim 19 comprising at least one component selectedfrom the group consisting of: an antiemetic, an alpha and/or betaadrenergic active compound, an analgesic, a muscle relaxant, a metabolicstimulant, caffeine, an antioxidant and an anti-inflammatory compound.21. A pharmaceutical composition identified in accordance with claim 6.22. The composition of claim 21 comprising at least one componentselected from the group consisting of: an antiemetic, an alpha and/orbeta adrenergic active compound, an analgesic, a muscle relaxant, ametabolic stimulant, caffeine, an antioxidant and an anti-inflammatorycompound.
 23. A pharmaceutical composition comprising a compoundproduced in accordance with claim
 18. 24. The composition of claim 23comprising at least one component selected from the group consisting of:an antiemetic, an alpha and/or beta adrenergic active compound, ananalgesic, a muscle relaxant, a metabolic stimulant, caffeine, anantioxidant and an anti-inflammatory compound.
 25. The pharmaceuticalcomposition of claim 22 in a delivery format selected from the groupconsisting of: pill, tablet, osmotic pump, ointment, inhalant, eye drop,sublingual substance, mouthwash, pastille, gel, hydrogel, injection,subdermal implant, powder, emulsion, elixir, gum, cream, paste,liniment, liposome, skin patch, suppository, IUD, microsphere,nanosphere and nasal spray.
 26. The composition of claim 23 comprisingat least one compound selected from the group consisting of:cannabigerolic acid (CBGA); cannabigerolic acid monomethylether (CBGAM);cannabigerol (CBG); cannabigerol monomethylether (CBGM);cannabigerovarinic acid (CBGVA); cannabigerovarin (CBGV),cannabichromenic acid (CBCA); cannabichromene (CBC);cannabichromevarinic acid (CBCVA); cannabichromevarin (CBCV);cannabidiolic acid (CBDA); cannabidiol (CBD); cannabidiolmonomethylether (CBDM); cannabidiol C₄ (CBD-C4); cannabidivarinic acid(CBDVA); cannabidivarin (CBDV); cannabidiorcol (CBD-C1);Δ⁹-tetrahydrocannabinolic acid A (THCA-A); Δ⁹-tetrahydrocannabinolicacid B (THCA-B); 6a,10a-trans-6a,7,8,10a-tetrahydro-6,6,9-trimethyl-3-pentyl-6H-dibenzo[b,d]pyran-1-ol, (Δ⁹-tetrahydrocannabinol,THC); Δ⁹-tetrahydrocannabinolic acid-C4 (THCA-C4);Δ⁹-tetrahydrocannabinol-C4 (THC-C4); Δ⁹-tetrahydrocannabivarinic acid(THCVA); Δ⁹-tetrahydrocannabivarinic (THCV);Δ⁷-cis-isotetrahydrocannabivarin; Δ⁹-tetrahydrocannabiorcolic acid(THCA-C1); tetrahydrocannabiorcol (THC-C1), Δ⁸-tetrahydrocannabinolicacid (Δ⁸-TCA); Δ⁸-tetrahydrocannabinol (Δ⁸-THC), cannabicyclol (CBL);cannabicyclolicacid (CBLA); cannabicyclovarin (CBLV), cannabiesoic acidA (CBEA-A); cannabiesoic acid B (CBEA-B); cannabieson (CBE),cannabinolic acid (CBNA); cannabinol (CBN); cannabinol methylether(CBNM); cannabinol-C4 (CBN-C4); cannabivarin (CBV); cannabinol-C2(CBN-C2); cannabiorcol (CBN-C1); cannabinodiol (CBND); cannabinidivarin(CBDV); cannabitriol (CBT);10-ethoxy-9-hydroxy-Δ-6a-tetrahydrocannabinol (10-EHDT);8,9-dihydroxy-Δ-6a-tetrahydrocannabinol (8,9-DHDT); cannabitriolvarin(CBTV); ethoxy-cannabitriolvarin (CBTVE), dehydrocannabifuran (DCBF);cannabifuran (CBF); cannabichromanon (CBCN); cannabicitran (CBT);10-oxo-Δ-6a-tetrahydrocannabinol (OTHC); Δ⁹-cis-tetrahydrocannabinol(cis-THC);3,4,5,6-tetrahydro-7-hydroxy-α-α-2-trimethyl-9-n-propyl-2,6-methano-2H-1-benzoxocin-5-methanol(2H-iso-HHCV); cannabiripsol (CBR); trihydroxy-Δ⁹-tetrahydrocannabinol(triOH-THC); at least one phytoantiinflammatory compound;N-acetylcysteine; at least one carotenoid selected from the groupconsisting of: β-carotene, lycopene, lutein, astaxanthin and zeaxanthin;L-cysteine; N-acetylcysteine and analogues and metabolic precursorsthereof; glutathione (GSH); coenzyme Q10 (CoQ10); α-lipoic acid;resveratrol; a flavonoid; milk thistle; gingko; biloba; gotu-kola; atleast one bioflavonoid selected from the group consisting of: 1,2dithiolane-3-pentanoic acid; lipoate (α-LΔ⁻), and dihydrolipoate (DLA⁻);vitamin E, vitamin C, riboflavin (B₂); L-creatine; L-arginine;L-carnitine; cyclosporin A; manganese; magnesium; zinc; carnosine;folinic acid; dichloroacetate and succinate.
 27. The composition ofclaim 25 wherein said at least one phytoantiinflammatory compound isselected from the group consisting of: curcumin, colchicine,resveratrol, capsaicin, epigallocatechin-3-gallate and quercetin. 28.The composition of claim 21 comprising at least one compound selectedfrom the group consisting of: cannabigerolic acid (CBGA); cannabigerolicacid monomethylether (CBGAM); cannabigerol (CBG); cannabigerolmonomethylether (CBGM); cannabigerovarinic acid (CBGVA);cannabigerovarin (CBGV), cannabichromenic acid (CBCA); cannabichromene(CBC); cannabichromevarinic acid (CBCVA); cannabichromevarin (CBCV);cannabidiolic acid (CBDA); cannabidiol (CBD); cannabidiolmonomethylether (CBDM); cannabidiol C₄ (CBD-C4); cannabidivarinic acid(CBDVA); cannabidivarin (CBDV); cannabidiorcol (CBD-C1);Δ⁹-tetrahydrocannabinolic acid A (THCA-A); Δ⁹-tetrahydrocannabinolicacid B (THCA-B); 6a,10a-trans-6a,7,8,10a-tetrahydro-6,6,9-trimethyl-3-pentyl-6H-dibenzo[b,d]pyran-1-ol, (Δ⁹-tetrahydrocannabinol,THC); Δ⁹-tetrahydrocannabinolic acid-C4 (THCA-C4);Δ⁹-tetrahydrocannabinol-C4 (THC-C4); Δ⁹-tetrahydrocannabivarinic acid(THCVA); Δ⁹-tetrahydrocannabivarinic (THCV);Δ⁷-cis-isotetrahydrocannabivarin; Δ⁹-tetrahydrocannabiorcolic acid(THCA-C1); tetrahydrocannabiorcol (THC-C1), Δ⁸-tetrahydrocannabinolicacid (Δ⁸-TCA); Δ⁸-tetrahydrocannabinol (Δ⁸-THC), cannabicyclol (CBL);cannabicyclolicacid (CBLA); cannabicyclovarin (CBLV), cannabiesoic acidA (CBEA-A); cannabiesoic acid B (CBEA-B); cannabieson (CBE),cannabinolic acid (CBNA); cannabinol (CBN); cannabinol methylether(CBNM); cannabinol-C4 (CBN-C4); cannabivarin (CBV); cannabinol-C2(CBN-C2); cannabiorcol (CBN-C1); cannabinodiol (CBND); cannabinidivarin(CBDV); cannabitriol (CBT);10-ethoxy-9-hydroxy-Δ-6a-tetrahydrocannabinol (10-EHDT);8,9-dihydroxy-Δ-6a-tetrahydrocannabinol (8,9-DHDT); cannabitriolvarin(CBTV); ethoxy-cannabitriolvarin (CBTVE), dehydrocannabifuran (DCBF);cannabifuran (CBF); cannabichromanon (CBCN); cannabicitran (CBT);10-oxo-Δ-6a-tetrahydrocannabinol (OTHC); Δ⁹-cis-tetrahydrocannabinol(cis-THC);3,4,5,6-tetrahydro-7-hydroxy-α-α-2-trimethyl-9-n-propyl-2,6-methano-2H-1-benzoxocin-5-methanol(2H-iso-HHCV); cannabiripsol (CBR); trihydroxy-Δ⁹-tetrahydrocannabinol(triOH-THC); at least one phytoantiinflammatory compound;N-acetylcysteine; at least one carotenoid selected from the groupconsisting of: β-carotene, lycopene, lutein, astaxanthin and zeaxanthin;L-cysteine; N-acetylcysteine and analogues and metabolic precursorsthereof; glutathione (GSH); coenzyme Q10 (CoQ10); α-lipoic acid;resveratrol; a flavonoid; milk thistle; gingko; biloba; gotu-kola; atleast one bioflavonoid selected from the group consisting of: 1,2dithiolane-3-pentanoic acid; lipoate (α-LA⁻), and dihydrolipoate (DLA⁻);vitamin E, vitamin C, riboflavin (B₂); L-creatine; L-arginine;L-carnitine; cyclosporin A; manganese; magnesium; zinc; carnosine;folinic acid; dichloroacetate and succinate.
 29. The composition ofclaim 28 wherein said at least one phytoantiinflammatory compound isselected from the group consisting of: curcumin, colchicine,resveratrol, capsaicin, epigallocatechin-3-gallate and quercetin. 30.The composition of claim 23 comprising at least one compound selectedfrom the group consisting of: cannabigerolic acid (CBGA); cannabigerolicacid monomethylether (CBGAM); cannabigerol (CBG); cannabigerolmonomethylether (CBGM); cannabigerovarinic acid (CBGVA);cannabigerovarin (CBGV), cannabichromenic acid (CBCA); cannabichromene(CBC); cannabichromevarinic acid (CBCVA); cannabichromevarin (CBCV);cannabidiolic acid (CBDA); cannabidiol (CBD); cannabidiolmonomethylether (CBDM); cannabidiol C₄ (CBD-C4); cannabidivarinic acid(CBDVA); cannabidivarin (CBDV); cannabidiorcol (CBD-C1);Δ⁹-tetrahydrocannabinolic acid A (THCA-A); Δ⁹-tetrahydrocannabinolicacid B (THCA-B);6a,10a-trans-6a,7,8,10a-tetrahydro-6,6,9-trimethyl-3-pentyl-6H-dibenzo[b,d]pyran-1-ol,(Δ⁹-tetrahydrocannabinol, THC); Δ⁹-tetrahydrocannabinolic acid-C4(THCA-C4); Δ⁹-tetrahydrocannabinol-C4 (THC-C4);Δ⁹-tetrahydrocannabivarinic acid (THCVA); A⁹-tetrahydrocannabivarinic(THCV); A′-cis-isotetrahydrocannabivarin; Δ⁹-tetrahydrocannabiorcolicacid (THCA-C1); tetrahydrocannabiorcol (THC-C1),Δ⁸-tetrahydrocannabinolic acid (Δ⁸-TCA); Δ⁸-tetrahydrocannabinol(Δ⁸-THC), cannabicyclol (CBL); cannabicyclolicacid (CBLA);cannabicyclovarin (CBLV), cannabiesoic acid A (CBEA-A); cannabiesoicacid B (CBEA-B); cannabieson (CBE), cannabinolic acid (CBNA); cannabinol(CBN); cannabinol methylether (CBNM); cannabinol-C4 (CBN-C4);cannabivarin (CBV); cannabinol-C2 (CBN-C2); cannabiorcol (CBN-C1);cannabinodiol (CBND); cannabinidivarin (CBDV); cannabitriol (CBT);10-ethoxy-9-hydroxy-Δ-6a-tetrahydrocannabinol (10-EHDT);8,9-dihydroxy-Δ-6a-tetrahydrocannabinol (8,9-DHDT); cannabitriolvarin(CBTV); ethoxy-cannabitriolvarin (CBTVE), dehydrocannabifuran (DCBF);cannabifuran (CBF); cannabichromanon (CBCN); cannabicitran (CBT);10-oxo-Δ-6a-tetrahydrocannabinol (OTHC); Δ⁹-cis-tetrahydrocannabinol(cis-THC);3,4,5,6-tetrahydro-7-hydroxy-α-α-2-trimethyl-9-n-propyl-2,6-methano-2H-1-benzoxocin-5-methanol(2H-iso-HHCV); cannabiripsol (CBR); trihydroxy-Δ⁹-tetrahydrocannabinol(triOH-THC); at least one phytoantiinflammatory compound;N-acetylcysteine; at least one carotenoid selected from the groupconsisting of: β-carotene, lycopene, lutein, astaxanthin and zeaxanthin;L-cysteine; N-acetylcysteine and analogues and metabolic precursorsthereof; glutathione (GSH); coenzyme Q10 (CoQ10); α-lipoic acid;resveratrol; a flavonoid; milk thistle; gingko; biloba; gotu-kola; atleast one bioflavonoid selected from the group consisting of: 1,2dithiolane-3-pentanoic acid; lipoate (α-LA⁻), and dihydrolipoate (DLA⁻);vitamin E, vitamin C, riboflavin (B₂); L-creatine; L-arginine;L-carnitine; cyclosporin A; manganese; magnesium; zinc; carnosine;folinic acid; dichloroacetate and succinate.
 31. The composition ofclaim 30 wherein said at least one phytoantiinflammatory compound isselected from the group consisting of: curcumin, colchicine,resveratrol, capsaicin, epigallocatechin-3-gallate and quercetin. 32.The method of claim 5 wherein said new pharmaceutical composition isapplied to treating a second symptom or second disease wherein saidsymptom is not identical to said second symptom or said disease is notidentical to said second disease.
 33. The method of claim 6 wherein saidnew pharmaceutical composition is applied to treating a second diseasewherein said first disease is not identical to said second disease. 34.The method of claim 18 wherein said new pharmaceutical composition isapplied to treating a second symptom or second disease wherein saidfirst symptom is not identical to said second symptom or said firstdisease is not identical to said second disease.